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Location: Tokyo, Japan About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Join Anthropic's Customer Success team as one of the founding members of our Japan Customer Success team as we pioneer the future of enterprise AI adoption. As a Customer Success Manager at Anthropic, you'll be the strategic partner and trusted advisor to our most complex customers across Japan, helping them harness the full potential of all our Claude capabilities: API, Claude for Enterprise, and Claude Code. You'll develop genuine partnerships with customers, gaining a deep understanding of their business objectives, strategic direction, AI vision, and technical needs. You'll draw on both your business acumen and technical expertise to serve as a strategic advisor throughout their journey with us. In partnership with the broader account team, you will help customers identify the right Claude capabilities for their specific business objectives. You'll work closely with them to provide best practices and guidance, and support them as their usage (consumption and seat based) grows and evolves. Your role focuses on helping customers scale their usage effectively, implement change management strategies, optimize use cases, and maximize the value of their investment through expanded use cases across their organization. The insights you gather from your customers will directly inform our research priorities, product development, and go-to-market strategies. That makes you a key voice in shaping how we build and deliver ongoing value as a business. As one of the founding members of our Customer Success team in Japan, you'll help shape how we build the function in-region. That includes establishing regional processes, developing new customer relationships, and representing Anthropic's brand in a high-growth market alongside a small, growing team. You'll operate with significant autonomy while maintaining strong alignment with global teams. This requires someone who thrives in ambiguous environments and can work effectively across time zones. Key responsibilities Build trusting, strategic relationships with key Japanese customer decision makers to understand their business and objectives, identifying opportunities for optimization and expansion Become an expert in Anthropic's products across API, Claude for Enterprise, and Claude Code, understanding the technical nuances and best practices for each to guide customers to the right solutions Leverage your deep knowledge of the customer and regional nuances to proactively drive usage planning, understanding current and future consumption and adoption and how it creates realized value for the customer Monitor usage patterns and identify optimization opportunities, proactively addressing underutilization across both our consumption-based and seat-based products to drive full value from contracted commitments Serve as the customer's thought partner, enhancing their knowledge of Claude products by socializing Anthropic's product roadmap, driving awareness of new products, and engaging Product PMs as the voice of Japanese customers Document and quantify customer value realized through business outcomes, ROI, and impact metrics to build compelling internal business cases for continued and expanded investment Identify potential use cases and lines of business not currently onboarded, partnering with customers to discover new applications for Claude across different departments, teams, and workflows Develop and execute change management strategies to drive end-user adoption and maximize value within customer organizations, including Train the Trainer programs, Center of Excellence development, and organizational enablement Own the customer experience across their lifecycle: manage comprehensive account and success plans grounded in the customer's business objectives, conduct Quarterly Business Reviews, and serve as the primary conduit between the customer and Anthropic Build Anthropic's brand and customer relationships as part of our founding in-region CS team, developing Japan-specific processes, playbooks, and best practices where needed that account for regional business cultures Minimum qualifications Experience in customer-facing roles (Customer Success, Consulting, Solutions Architect, Solutions/Functional Consultant, Success Engineer or similar) Technical fluency with ability to understand and articulate AI/ML concepts, API integrations, and software implementation patterns Experience explaining and demonstrating technical products to various audiences Strong project management skills and ability to manage multiple customer relationships Passion for AI and interest in responsible development of advanced systems Fluency in English and Japanese Preferred qualifications 6+ years of experience in relevant field Experience driving success across both consumption-based and seat-based business models, with understanding of different expansion levers and success metrics for each Strategic mindset to identify growth opportunities and translate them into actionable expansion plans Cross-functional collaborator who represents the customer in a positive, proactive manner, rallying everyone around paths forward that solve customer needs Experience working in and building a growing region, while navigating across time zones with US-based headquarters A knack for bringing order to chaos and an enthusiastic "roll up your sleeves" mentality. You are a true team player Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Georgia; Ukraine; Poland; Brazil; Argentina; Colombia Workplace: Remote Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. We are looking for a Senior Software Engineer (Elasticsearch, Scala) to join a team powering food search and logging for one of the world’s leading health and nutrition platforms. You’ll contribute directly to the systems that drive search — backend services, search infrastructure, and experimentation — with a focus on improving core metrics: conversion rates, time to log, query abandonment, and result relevance. WHAT YOU’LL DO - Contribute to, build, and maintain backend services that drive the food search experience, integrating with systems across the broader engineering organization. - Perform search performance tuning end-to-end — data design, indexing, query evaluation, and iterative improvement within Elasticsearch. - Assist in the evaluation and implementation of search and data technologies that improve result quality and user experience. - Collaborate closely with senior search engineers, product management, and leadership on solution discovery, experiment planning, and delivery. - Contribute to the development of tools, processes, and metrics for measuring and monitoring search quality. REQUIRED SKILLS & EXPERIENCE Elasticsearch - Demonstrated experience with performance tuning, query analysis, and relevance optimization in Elasticsearch at scale. - Strong understanding of index design, mapping strategies, cluster management, and scoring/ranking mechanics. - Familiarity with high availability, disaster recovery, and operational monitoring for Elasticsearch clusters. - Ability to deploy new indexes or clusters as needed for load balancing or experimentation. - Ability to translate product specifications into technical requirements and deploy ranking and relevance experiments with clearly defined success criteria and metrics. Scala - Strong experience writing, shipping, and maintaining Scala services in production. - Comfortable working across a stack that also includes SQL and Python — Scala is the primary language for this engagement. Agentic development - Active user of AI development tools such as Claude Code, Cursor, or comparable AI-powered coding environments — shipping production code with them, not just using autocomplete. - Familiarity with agentic coding patterns and workflows — code generation, refactoring, debugging, and test authoring. - Able to articulate how AI tooling fits into their development process and where human judgment remains critical. Engineering fundamentals - First-hand experience building, scaling, and supporting large-scale data infrastructure systems in production. - Strong understanding of database design, data architecture, and performance tuning across multiple data stores — MySQL, MongoDB, DynamoDB, Redis, or similar. - Experience with high-volume messaging systems such as Kafka. - Familiarity with AWS, GCP, or other cloud platforms. - Strong peer code review practices. PREFERRED QUALIFICATIONS - Experience leveraging AI workflows for meaningful development acceleration beyond autocomplete — code generation, refactoring, debugging, and test authoring at scale. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Location: Reykjavík We're looking for a staff software engineer to work on how data is queried and who is allowed to see it. Every read in Asana passes through this layer: it resolves what a user is asking for and enforces, on every object, whether that user is permitted to see it. You will help us keep those guarantees correct and fast as our largest customers grow their domains, their permission structures get more intricate, and AI agents become a significant new class of caller. The Query and Access Control team owns the query execution path over the Work Graph and the permissioning model that governs it. As a staff engineer on the team, you will take on our hardest technical problems and drive the work that spans several teams, bringing depth to the design decisions that shape this layer for years. We work closely with other teams in the core infrastructure area to build and retain customer trust in Asana as the platform for their critical workflows. This role is based in our Reykjavik office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you'll achieve Design and implement a query layer over the Work Graph that stays correct and performant as customer domains and permission structures grow Evolve our access control model so that permission checks remain sound, auditable, and fast on every read path Define how new classes of caller, including AI agents acting on a user's behalf, are authorized, without weakening the guarantees customers depend on Drive large, multi-quarter projects that cut across team boundaries, from design and implementation through deployment and iteration Build alignment on the design with engineers and leaders in other teams before the code is written, and keep that alignment as the work lands Share what you know through design review, code review, and mentorship Partner with infrastructure teams across Asana to define how user data in the Work Graph is accessed Support framework and product engineers to build new product functionality at scale, quickly About you 8+ years of engineering experience building and operating reliable backend services at scale, with 3+ years driving large-scale projects You have driven large technical initiatives spanning multiple teams, and perhaps organizations, from early design to adoption You go deep on hard problems and can carry a design from first principles through to production You enjoy sharing what you know with other engineers and helping them build production-quality infrastructure You are skilled at communicating technical concepts and constraints to cross-functional partners in product You bring care and rigor to systems where correctness is not negotiable, and can reason about the blast radius of a change before it ships Desirable You have experience with authorization systems, permission models, or multi-tenant data isolation at scale You have worked on query engines, query planning, caching layers, or graph-shaped data access You are familiar with infrastructure-as-code and container orchestration technologies like Terraform and Kubernetes At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply. What we’ll offer Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit. For this role, the estimated base salary range is between 1 600 000 - 1 800 000 ISK monthly. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified. In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role. We strive to provide equitable and competitive benefits packages that support our employees worldwide and include: Mental health, wellness & fitness benefits Career coaching & support Inclusive family building benefits Long-term savings or retirement plans In-office culinary options to cater to your dietary preferences These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role. #LI-Hybrid #LI-AZ About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law. Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

Location: Tel Aviv-Yafo, Tel Aviv District, Israel About Aidoc Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year. Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions. Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need. About this role We are looking for an experienced Engineering Team Lead to build and lead the FirstRead team , a new product-focused team within Aidoc’s Imaging Platform group. FirstRead, Aidoc’s report-generation initiative, is one of the company’s most important and high-potential new products. We have decided to found this team, following a highly successful product beta, in which our AI drafted thousands of full radiology reports, covering hundreds of different clinical findings with near-human accuracy. The product is evolving rapidly, and so will the team around it. With the opportunity to shape the product and its technical direction from the ground up, the FirstRead team will be accountable for the product outcome end-to-end . The team will work across the stack, using existing platform capabilities where possible, evolving them where needed, and building new services and capabilities when required. This is a role for a TL who enjoys shaping new products and turning evolving opportunities into clear technical direction. The team’s scope, architecture, priorities, and  longer-term mission will evolve as we learn. You will play a central role not only in delivering FirstRead, but also in building the team itself and shaping how product-focused teams operate within Imaging Platform . You will work closely with Product, AI teams, and other engineering teams across Imaging Platform to turn rapidly evolving product needs into working software, while balancing speed, technical quality, and long-term platform considerations. Responsibilities End-to-End Ownership: Lead the engineering effort required to make FirstRead successful, across engineering disciplines including  backend, frontend, AI infrastructure, DICOM pipelines, existing platform services, and entirely new components. Creating Clarity in a Fast-Moving Environment: Turn changing product needs and incomplete information into technical direction, priorities, and executable plans. Continuously adapt as the product evolves. Technical Leadership: Drive architecture and technical decisions across a broad technical surface. Know when to move quickly, when to invest in robust solutions, and when to involve domain experts. Cross-Team Engineering: Work closely with other TLs and engineers across Imaging Platform. Enable the team to contribute to existing services and platforms while respecting their architecture, ownership, and long-term direction. Team Building: Build the FirstRead engineering team, establish its culture and ways of working, develop engineers, and help shape its longer-term mission as a product-focused team. Delivery and Product Partnership: Partner closely with Product and other stakeholders, taking ownership of turning evolving product direction into concrete engineering execution. Engineering Excellence: Maintain strong engineering standards while operating in a fast-moving environment, balancing experimentation and delivery speed with reliability, maintainability, and scalability. Requirements Senior hands-on software engineering experience , including experience building complex systems end-to-end. Exceptional track record leading engineering teams , while remaining actively involved in technical and architectural decisions. Strong sense of urgency, with the ability to drive execution and maintain momentum in fast-paced, high-priority projects. Proven ability to lead projects in ambiguous, rapidly changing environments , where requirements and technical direction are not fully defined upfront. Broad technical experience and passion for working across different areas of the stack rather than specializing exclusively in a single domain. Strong system design and software engineering fundamentals, with experience designing and building distributed production systems. Demonstrated ability to take ownership of an outcome from early concept through implementation, production, and continued evolution . Excellent collaboration and communication skills, with demonstrated ability to work effectively across engineering teams and organizational boundaries. Strong product and business orientation, with the ability to balance technical considerations with speed, learning, and business impact. Strong leadership, mentorship, and team-building skills. Advantages Experience working in an environment with shared platforms and multiple engineering teams contributing to the same product. Experience across multiple areas such as backend, frontend, cloud infrastructure, data pipelines, or AI/ML systems. Experience with AI-powered products or production AI systems. Working at Aidoc Our Perks: Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives) We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees. Amazing and healthy breakfasts and lunches prepared daily by our personal chef! Stocked up kitchen & meal card Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes. Amazing culture - collaborative, transparent & fun! Attractive compensation package & benefits Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

Location: India Workplace: Remote ABOUT ELEVENLABS ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always. We have expanded from voice into three main platforms: - ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. - ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. - ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. HOW WE WORK - High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. - Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. - AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. - Excellence everywhere: Everything we do should match the quality of our AI models. - Global team: We prioritize your talent, not your location. WHAT WE OFFER - Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. - Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities. - Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend. - Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose. - Annual team offsite: Each year, we bring your entire team together in a new location - past offsites have included Croatia, Italy and Cancún - Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend. ABOUT THE ROLE We’re looking for a highly motivated, self-starter Account Executive based in India who is passionate about AI technology and how it is changing businesses. We don’t just sell a product or custom-level solutions; we are partnering with enterprises to help them generate new experiences and monetisation opportunities at scale with our breakthrough voice technology. In this role you will: - Build and manage a growing portfolio of new Mid Market accounts in the Customer Experience and Conversational AI Experiences spaces to help ElevenLabs meet its revenue goals. - Identify new business opportunities in that align with ElevenLabs’ product offering and roadmap. - Generate leads, negotiate contracts and close sales in collaboration with the Growth team. - Develop and maintain a deep understanding of the Conversational AI industry - Be responsible for KPI and sales performance tracking, providing weekly updates to the wider ElevenLabs team. WHO YOU ARE We're looking for exceptional individuals who combine technical excellence with ethical awareness, who are excited by hard problems and motivated by human impact. You’ll strive with us if you: - Are passionate about audio AI driven by a desire to make content universally accessible and breaking the frontiers of new tech. - Are a highly motivated and driven individual with a strong work ethic. Our team is aware of this critical moment of audio AI evolution and is committed to going the extra mile to lead. - Are analytical, efficient, and strive on solving complex challenges with a first principles mindset. - Consistently strive for excellence, delivering high-quality work quickly and exceeding expectations. - Take initiative and work autonomously from day one, prioritizing learning and contribution while leaving ego aside. WHAT YOU BRING - Builds plan to quota in first sales and upsells out of NAL - Experience in building a new category, company, product in a space with previously no penetration - ~ 7-11 years of experience in value selling a technology product, preferably in Customer Experience and Customer engagement to clients with a global footprint - Generate self-led pipeline in target list of accounts - Network and experience in the IN CX, Support and BPO industry and has sold to CXOs - Close deals and manage customer onboarding/delight - Showed previous ownership for all aspects of the customer lifecycle including onboarding, and support - Evidence of farming accounts to deliver multi-X growth - Worked at a Top tier growth company where there is a keen understanding of sales process and high degree of ownership - Drive initiatives that improve ElevenLabs consideration - Has performed sales development activities such as campaigns, events, partnerships that drive ElevenLabs consideration with customers - Self Starter - Analytical skills and proficiency with spreadsheets - Proficiency in creating compelling presentations and demos - Market Insight: Deep knowledge of the IN CX, Support and BPO industry - Proficiency in English - Plus: Network in the relevant SIs/consults LOCATION: MUMBAI, IN #LI-Remote We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

Location: New York City, NY; New York City, NY | Seattle, WA; Remote-Friendly, United States; San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is looking for Software Engineers to join the Memory & Search team. We own how Claude remembers you and how it finds what it needs, across Claude.ai, Cowork and Claude Code. That spans the user-facing experience (what Claude remembers, how people see and edit it, how search surfaces the right conversation) and the shared infrastructure underneath it, the memory service, indexing, retrieval and vector search. Memory is one of the biggest levers on whether Claude feels like it knows you. We recently moved memory from a periodically synthesized summary to a dynamic, editable, on-demand system, and then unified it so the same memory follows you across products. Search went from a top user complaint to something people rely on to find past work. The platform is now in place, and the next phase is finding the product form factors that make memory the most compelling and sticky part of using Claude. That is why we are hiring product engineers. The team is strong on infrastructure, and we want people who have shipped user-facing products at scale, have a sharp sense for what makes a product feel good, and have built agentic systems where the model, the tools and the user interface have to work together. You will run short, demo-driven experiments on top of the memory and search stack, decide what to keep based on real usage, and help the whole team think like a product team. If you have founded a company, been an early engineer at a startup, or taken a product from zero to one, you will recognize the way we want to work. This is a trust-sensitive surface. Memory touches privacy, consent and enterprise controls, so you will work closely with product, design, privacy, legal and safeguards, and you will be expected to treat those constraints as part of good product design rather than obstacles to it. Key responsibilities Design, build and ship memory and search experiences in Claude.ai, Cowork and Claude Code, owning them end to end from the backend service through the model's tools to the user interface Run product experiments on the memory and search stack: form a hypothesis, build a demo, put it in front of real users, measure, and make a clear persevere-or-pivot call Shape how Claude uses memory and retrieval inside its agentic loop, including what the model stores, when it searches, how results are ranked and presented, and how the user stays in control Define and track the metrics that tell us whether memory is actually making Claude more useful, and build the evaluations that keep quality honest as the system evolves Improve search relevance and recall across conversations and memories, working across embeddings, hybrid retrieval and ranking as well as the interface that presents results Partner with product, design, privacy, legal and safeguards to ship features that respect user consent and enterprise requirements such as customer-managed encryption keys and data retention policies Raise the bar on product quality for the team through design reviews, code reviews and the standards you set for latency, polish and reliability Share the on-call for the systems you own Minimum qualifications Experience building and operating user-facing products used by a large number of people, including the backend services behind them Experience building agentic systems or LLM-powered products, including tool use, retrieval and prompt or context design Strong programming skills in Python and TypeScript, with experience across backend services and web front ends A track record of taking a product or feature from an idea to launch, and iterating on it based on usage data and user feedback Experience defining product metrics and running experiments to make decisions Strong product judgment: you notice when something feels off and you fix it, and you can explain why a design choice matters to users Strong written and verbal communication, with experience working closely with product managers, designers and non-engineering partners Interest in AI safety and Anthropic's mission Preferred qualifications Experience as a founder, early-stage engineer, or someone who has taken a product from zero to one Experience building search or retrieval systems: embeddings, vector search, hybrid lexical and semantic retrieval, or ranking Experience building evaluations for LLM or ML systems, or measuring the quality of retrieval and ranking Experience on consumer products with strong retention, or on personalization systems Experience shipping features that handle sensitive data or meet enterprise requirements such as customer-managed encryption keys, data residency or HIPAA Experience with latency-sensitive, performance-critical product work Experience mentoring engineers or setting technical direction for a team The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote - US About Backblaze Backblaze is the object storage leader in the open cloud movement, fueling customer success with cloud storage built purposefully to unlock budgets, unburden administrators, and unleash innovators. Together with our partners, we’re helping customers break free from the restrictive, overpriced legacy solutions that hold them back, and blaze forward with the full power of the open cloud in their hands. Founded in 2007, we scaled the business with less than $3 million in outside funding until 2021, when we did a traditional IPO on the Nasdaq stock exchange. Today, Backblaze generates over $136M ARR and is the leading specialized storage cloud, managing over three billion gigabytes of data storage for 500K+ customers in 175+ countries, including businesses, developers, IT professionals, and individuals. But while there is a lot to celebrate in our past, there is almost as much opportunity ahead of us. We’re seeking a Principal SRE to join our team! About the Role We are seeking a Principal Site Reliability Engineer (SRE) to help ensure the stability, scalability, and reliability of our production systems. The ideal candidate will have extensive experience collaborating in cross functional teams to manage the design, implementation and ongoing management of the Backblaze core infrastructure. You will be approved to demonstrate strong observability skills, process and service improvement and ability to leverage AI and automation to assist to mitigate issues faster and meet customer demand.. As a technical leader in Backblaze you will be expected to work across the organisation to achieve our goals. This will include working with our executives and customers. The role will focus long term strategic focus on platform stability. Key Responsibilities Service Reliability & Operations Own the availability and durability of critical services across production environments and accountability for outcomes. Ability to work independently, take ownership, and drive projects from problem discovery through resolution. Assist and advise on the design of service health metrics using SLIs, SLOs, and error budgets, and escalate issues when thresholds are at risk; partner with service owners to define/iterate SLIs/SLOs and establish error budget policies and alerting. Participate in leadership on-call rotations, incident response, and post-incident reviews to drive service improvements. Follow established ITIL/OSS processes (incident, change, problem, and capacity management). Architect and Design Design automation for common operational tasks, reducing manual intervention and toil. Collaborate with engineering on overall storage design, performance expectation against product SLAs. Define the monitoring, logging, and alerting frameworks (e.g., Prometheus, Grafana, Catchpoint, ELK), and help integrate runbooks with FireHydrant. Work with CI/CD pipelines, configuration management, and infrastructure as code tools (Terraform, Ansible, Jenkins). Write scripts (Bash, Python, Go, etc.) to improve system reliability and efficiency. Collaboration Partner with engineering, customer success, product, and operations teams to support resilient system design and operations. Work with customers to ensure stability prioritization is based around their needs and experiences in using Backblaze products. Work with vendors and service providers to troubleshoot service issues and track SLA performance. Document systems, share learnings, and help grow a reliability-minded engineering culture. Continuous Improvement Lead cross functional teams to identify gaps in observability, operations process and define overall prioritization strategy. Identify recurring issues and propose long-term improvements, and design action plans around implementing those improvements. Promote reliability-focused practices within development and operations teams. Qualifications Education & Experience Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience). 10+ years of experience in site reliability, systems engineering, or operations, experience with hyperscalers preferred. Exposure to large-scale, production-grade systems, including experience establishing operational procedures or runbooks and bringing others up to speed on them. Technical Skills Solid Linux systems administration and troubleshooting skills. Proven ability to leverage AI tools to improve platform stability and scalability. Knowledge of storage systems, performance, sharding and storage algorithms. Experience in load balancing services including IPVS. Security-minded operations (patching, hardening, identifying vulnerabilities). Familiarity with service reliability concepts — monitoring, alerting, incident response, and root cause analysis. Proficiency in at least one scripting language (Python, Bash, or Go). Experience working with containers (Kubernetes, Docker) and microservices concepts required; comfortable operating in a Kubernetes/Vitess-on-K8s environment (kubectl, mysqlsh, Vitess keyspaces). Experience with Hashicorp products (Nomad, Vault, Terraform). Preferred Attributes Experience in a SaaS, service provider, or distributed systems environment. Familiarity with ITIL/OSS practices and SLO/SLA’s. Strong problem-solving skills and willingness to learn new technologies. Experience with cloud platforms (AWS, GCP, or Azure). Backblaze Perks Healthcare for family, including dental and vision Competitive compensation and 401K RSU grants for full-time employees ESPP program Flexible vacation policy Maternity & paternity leave MacBook Pro to use for work, plus a generous stipend to personalize your workstation Childcare bonus (human children only) Fertility treatment and support Learning & development program Commuter benefits Culture that supports a healthy work-life balance Pay Transparency To provide greater transparency to candidates, we share pay ranges for all US-based job postings regardless of state. Final offer amounts are determined by multiple factors including candidate location, skills, depth of work experience, and relevant licenses/credentials. The pay range for this position is $215,000 to $250,000 per year. At Backblaze, we value being fair and good to our customers, partners, and employees. That’s why diversity, equity, and inclusion are at the core of our values. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education. We believe that our dedication to cultivating a diverse workspace not only allows us to better serve our customers in over 175 countries but further reinforces our commitment to doing the right thing. We are proud to be an Equal Opportunity Employer. To understand more about the data we collect and process as part of your application, please view our Backblaze Employee Privacy Notice.

Location: Tokyo, Japan Workplace: Hybrid WHO WE ARE Notion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. ABOUT THE ROLE: In this position, you'll play a crucial role in shaping our go-to-market strategy and driving data-informed decision-making within the Japan/APAC region. This position sits at the intersection of sales, strategy, and operations, offering the opportunity to significantly impact Notion's growth trajectory. You'll work closely with sales leadership and cross-functional teams to optimize processes, deliver actionable insights, and support key strategic initiatives. You will report directly to the Head of Field Strategy & Operations. WHAT YOU'LL ACHIEVE: - Partner with Japan leadership team to define and drive strategy (e.g. territory mapping, long-term account planning, geographic expansion) and results for the region by conducting insightful analysis on local Japan markets and customers while providing support for other APAC priorities as needed. - Support regional sales leaders and sales teams in achieving their goals by providing actionable insights and visibility to sales performance metrics - Build reporting and presentations for Japan/APAC sales leadership to update on the state of the business, both up and across the organization - Act as a partner to the Japan/APAC sales team, providing hands-on operational support to drive deals forward and advising with decision-making - Enable smooth, efficient deal execution by supporting day-to-day deal operations, including opportunity hygiene, quote preparation, and coordination of approvals and internal handoffs, helping sellers navigate processes and remove friction throughout the deal lifecycle - Partner with the GTM Systems team to continuously enhance our sales technology stack to provide both a best-in-class experience for our sellers and a robust sales data environment - Work with cross-functional teams including Legal, Finance, Product, Marketing, etc. as the primary operational counterpart on behalf of the Japan/APAC sales org - Maintain and embed global sales policies, processes, and procedures, driving discipline with regards to strategy execution - Support global planning process locally, including target setting, capacity modeling, territory carving, etc. - Surface on-the-ground observations and insights to global sales and RevOps leadership SKILLS YOU'LL NEED TO BRING: - 5+ years of strategy, operations, and analytics experience with a track record of driving growth - working in sales operations, preferably in a high-growth SaaS environment - Expertise to quickly drill down into the business funnel for outbound and inbound sales motions, and how that connects to revenue - Excellent analytical and quantitative modeling skills; ability to analyze and interpret data, provide actionable insights, and deliver measurable results - Expert proficiency with core sales tools (e.g. Salesforce, Gong, Outreach, etc.) and best practices for sales data management - Ability to apply AI-powered tools to accelerate analysis, uncover trends, and translate complex sales data into actionable business insights. Comfortable framing analytical questions, iterating on prompts, and validating AI-generated outputs with sound business judgment and rigorous data checks, while handling sensitive information responsibly - Strong collaborator, works well with stakeholders, gains trust, enjoys working with people - Demonstrates a senior presence and can convey complex information to executives clearly and concisely; can resolve tradeoffs. Effective communicator across levels and audiences - Hands on and proactive, with a builders mentality. - Maintaining high ownership mentality, demonstrated by developing projects of >6-12 months length - Notion power user or desire to learn -- prior Notion experience is not required, but you have the ability and desire to become a pro #LI-Onsite A NOTE ON AI You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on. EQUAL OPPORTUNITY & ACCOMMODATIONS We hire talented people from a wide range of backgrounds. If you’re excited about this role but don’t meet every bullet, we still encourage you to apply. Notion is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Consistent with applicable law, we will consider for employment qualified applicants with arrest and conviction records. Notion provides reasonable accommodations during the application process; if you need one, please let your recruiter know. Notion is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Notion considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Notion is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, please let your recruiter know.

Location: San Francisco; Seattle; New York City ABOUT THE ROLE The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes. This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate. KEY RESPONSIBILITIES - Build realistic enterprise evaluation environments spanning connected applications, representative datasets, user roles, and permissions, with complex, multi-step workflows and reproducible system state. - Own evaluation infrastructure, task suites, and automated graders that measure how well agents complete enterprise work, calibrated against human judgment and grounded in end-to-end outcomes. - Analyze agent trajectories and production failures, identify root causes, and ship improvements across the agent harness, tools, and skills that measurably improve task success and reliability. - Develop reusable skills and improve tool descriptions, schemas, and result handling so agents can select the right tools, execute workflows correctly, and recover from errors with fewer unnecessary calls. - Build and evaluate model-selection and routing strategies that match each task to the right model and effort level, balancing quality, latency, reliability, and cost. - Improve agent efficiency through context management, skill loading, caching, and execution strategies that reduce wasted tokens and cost per successful task without compromising quality or safety. - Build regression gates and launch-readiness signals for model, connector, tool, skill, and harness changes, and validate that evaluation gains translate into better production outcomes. QUALIFICATIONS - 5+ years of software engineering or machine learning engineering experience, with a track record of owning complex production systems from design through deployment and operation. - Strong system design skills, including building reliable, scalable infrastructure for experimentation, evaluation, or data-intensive applications. - Strong proficiency in a backend language such as Python, Go, or Rust, and the ability to work effectively across a multi-language production stack. - Hands-on experience building, evaluating, or improving LLM-based applications or agents, including tool use and multi-step workflows. - Deep expertise in at least one of the following: - Evaluation infrastructure, benchmark design, and automated grading. - Agent harnesses, tool interfaces, and reusable skills for complex workflows. - Realistic test environments or simulations spanning multiple systems, datasets, permissions, and stateful workflows. - Model selection, routing, and inference efficiency, including context management and caching. - Strong experimental and statistical judgment, including choosing representative tasks, defining meaningful success criteria, diagnosing failures, and distinguishing real improvements from noise. - Sound technical judgment in balancing task quality, latency, reliability, and cost, with a track record of translating evaluation findings into shipped improvements. - A track record of leading ambiguous, cross-team initiatives from architecture through production adoption, setting technical direction, and raising engineering quality through mentorship. If you’re excited about this role, we encourage you to apply even if you don’t meet every qualification. We value demonstrated impact, deep ownership, and the initiative to turn ambiguity into results.

Location: San Francisco; Seattle; New York City ABOUT THE ROLE The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes. This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate. KEY RESPONSIBILITIES - Build realistic enterprise evaluation environments spanning connected applications, representative datasets, user roles, and permissions, with complex, multi-step workflows and reproducible system state. - Own evaluation infrastructure, task suites, and automated graders that measure how well agents complete enterprise work, calibrated against human judgment and grounded in end-to-end outcomes. - Analyze agent trajectories and production failures, identify root causes, and ship improvements across the agent harness, tools, and skills that measurably improve task success and reliability. - Develop reusable skills and improve tool descriptions, schemas, and result handling so agents can select the right tools, execute workflows correctly, and recover from errors with fewer unnecessary calls. - Build and evaluate model-selection and routing strategies that match each task to the right model and effort level, balancing quality, latency, reliability, and cost. - Improve agent efficiency through context management, skill loading, caching, and execution strategies that reduce wasted tokens and cost per successful task without compromising quality or safety. - Build regression gates and launch-readiness signals for model, connector, tool, skill, and harness changes, and validate that evaluation gains translate into better production outcomes. QUALIFICATIONS - 5+ years of software engineering or machine learning engineering experience, with a track record of owning complex production systems from design through deployment and operation. - Strong system design skills, including building reliable, scalable infrastructure for experimentation, evaluation, or data-intensive applications. - Strong proficiency in a backend language such as Python, Go, or Rust, and the ability to work effectively across a multi-language production stack. - Hands-on experience building, evaluating, or improving LLM-based applications or agents, including tool use and multi-step workflows. - Deep expertise in at least one of the following: - Evaluation infrastructure, benchmark design, and automated grading. - Agent harnesses, tool interfaces, and reusable skills for complex workflows. - Realistic test environments or simulations spanning multiple systems, datasets, permissions, and stateful workflows. - Model selection, routing, and inference efficiency, including context management and caching. - Strong experimental and statistical judgment, including choosing representative tasks, defining meaningful success criteria, diagnosing failures, and distinguishing real improvements from noise. - Sound technical judgment in balancing task quality, latency, reliability, and cost, with a track record of translating evaluation findings into shipped improvements. - A track record of leading ambiguous, cross-team initiatives from architecture through production adoption, setting technical direction, and raising engineering quality through mentorship. If you’re excited about this role, we encourage you to apply even if you don’t meet every qualification. We value demonstrated impact, deep ownership, and the initiative to turn ambiguity into results.

Location: Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Utilization improvements are worth enormous sums at our scale. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at exabyte scale. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Utilization improvements are worth enormous sums at our scale. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at exabyte scale. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Mexico City, Cuauhtémoc, Mexico Working at Bitso We are a diverse team that takes pride in understanding the perspectives of others. We fully embrace working remotely and we are eager to act, improve and drive rapid progress inside and outside of our organization. To drive revolutionary changes in society and make crypto useful, we delight our customers with world-class products, deep care, and intentional empathy. Your Purpose As an Onboarding Operations Analyst, you will be responsible for supporting the customers registration and onboarding process within Bitso Business. You will actively manage the workflow for account registration, ensuring efficiency and compliance while contributing to strategic improvements that enhance scalability. Your insights will play a key role in enabling Bitso Business accounts to become fully operational. Collaborating cross-functionally, you will optimize workflows, streamline processes, and ensure the seamless execution of daily operations. Your role will be essential in identifying bottlenecks, improving system performance, and driving continuous enhancements across our platform. Also, you are going to be responsible to give support to customers with issues related with access to their accounts, 2FA reset, data updates and so on. Location Mexico City Reports To Business Operations Manager What You Will Do Review and process customer applications for Bitso Business accounts, ensuring all required documents are submitted and validated. Identify inefficiencies in the onboarding process and suggest improvements. Work with tech teams to automate manual processes for faster customer activation. Coordinate with KYB, Compliance, Legal, Fraud, and Tech teams to resolve onboarding issues. Ensure seamless communication between internal teams to accelerate approvals. Assist customers with onboarding-related questions and troubleshoot registration issues. Provide guidance on documentation requirements and eligibility criteria. Track key onboarding metrics such as approval rates, processing times, and bottlenecks. Provide insights to improve efficiency and enhance customer experience. Proactively identify areas for enhancement and contribute to operational strategies. Give support after the account onboarding, with issues related to the accounts access, the activation of new products, data updates… Qualifications 2+ years of experience in an Operations Analyst or similar role. Strong analytical skills and experience with ticket service tools (e.g., Jira, Zendesk). Ability to identify inefficiencies and propose effective solutions to improve processes. Experience tracking threads and customer requests via Slack or email Capability and great communications skills to manage support meetings with customers when necessary. Experience in working with cross-functional teams and managing multiple stakeholders. Knowledge of the cryptocurrency or fintech industry is a plus . Excellent organizational, communication, and time management skills. Ability to adapt in a fast-paced environment and work with evolving priorities. Who We Are With over 10 million users, Bitso is the leading cryptocurrency platform in Latin America. We are developing the cryptocurrency ecosystem in the region and enabling financial inclusion. We believe crypto is the future of finance, and we’re committed to making it useful by providing equal access to safe and intuitive financial products. We are here to make a lasting impact on our customer’s lives and we do so by embracing our core values: Be Human: we delight our customers through great products, deep care and true empathy. We are humble and we take pride in understanding the views of others to help us see the full picture. Drive Change: we're fearless pioneers committed to unlocking the crypto revolution for humanity. We move fast, take risks and work together to drive lasting impact. Choose Bold Honesty: we seek the truth, especially when it’s uncomfortable, in our teams, products and business reality because that will uncover where we need to focus. Be an Owner: our sense of urgency makes us have a bias towards action, where we prioritize exceptionally and are wise in allocating our time to ensure we always deliver creative and innovative results. Learn more about our culture and values . Compensation & Benefits At Bitso, you are taking the front seat on the edge of crypto innovation, creating the next generation of crypto-powered products. So for those willing to commit, adapt and pioneer the most important change of the century we offer: Me Time program , including unlimited paid time off. Employee Stock Option program. Extended Family Leave policy: all birthing parents, non-birthing parents and adopting parents are eligible for a 4-months leave. Premium health, dental and life Wellness platform. Want to leave an undoubtedly legacy with us? Fasten your seatbelt and join this spaceship, where you will find exponential growth and the opportunity to thrive!

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From “How do I fix a leaky faucet?” to “What should I watch next?”, the Answers Relevance team leverages AI to connect people with the real-world wisdom of Reddit communities. We’re hiring Senior and Staff Machine Learning Engineers to make Answers smarter, more relevant, and more helpful. Our SOTA AI systems helps surface the right conversations, but the heart of Answers is still people helping people ~ Redditors sharing what they know with each other! What You’ll Work On You’ll lead ML projects from idea to production, partnering with Product, Data Science, and Engineering across recommendations, search, messaging, and AI systems. You don’t need experience in every area listed below. A background in a few may make you a great fit! Recommendations, search, content understanding, or large-scale data and ML infrastructure SOTA large scale RecSys Foundational retriever models RAG systems, retrieval methods, LLM evaluation, or production LLM features Agentic AI, such as tool calls, MCPs, multi-agent systems, or orchestration Self-hosted open-weight models such as Qwen or Llama; prompt engineering, fine-tuning, post-training, or prompt optimization Improving grounding, instruction following, and hallucination; evaluating retrieval and generation quality Scaling LLM systems, including latency, caching, and cost; safety measures for prompt injection and unsafe inputs Defining product success metrics, feedback loops, and evaluation approaches, including human review What You’ll Do Build and improve large-scale ML systems, including retrieval and ranking, embeddings, and LLM-powered features Set technical direction and deliver measurable user and business impact Work with partner teams to shape product and technical roadmaps Evaluate new AI/ML approaches and support responsible LLM development Mentor engineers and contribute to long-term ML planning Required Qualifications 4–12 years of experience building, deploying, and operating ML systems in production Broad knowledge of ML fundamentals and experience applying them in production; expert-level modeling depth isn’t required Experience developing and productionizing models with TensorFlow, PyTorch, or Hugging Face Transformers Experience writing production-quality code, including testing, evaluation, and monitoring; Python experience required, Golang experience a plus Experience with ML systems such as data pipelines, feature engineering, model training and serving, and production monitoring Strong communication and collaboration skills, and a record of delivering measurable product impact Benefits Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave #LI-Remote Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $216,700 — $322,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: New York, NY or Chicago, IL About Us: EvolutionIQ builds AI that helps insurance claims teams handle claims more accurately, fairly, and efficiently, so more people impacted by injury or illness can get back to their lives with dignity and stability. As part of CCC Intelligent Solutions (NASDAQ: CCC), we pair AI-native product development with something almost no one else in this market has: 40 years of proprietary data and deep relationships with the largest, most complex carriers in the world. It's a rare combination, and it's what lets us build products others can't. Our people come first, and we think it shows. We've been named one of Inc.'s Best Workplaces three years running, plus Built In's Best Places to Work in 2025 and 2026. About the Role: As a Senior Technical Recruiter / TA Partner, you will own full-cycle recruiting for complex, high-impact Engineering and AI positions. You will lead searches for Senior Software Engineers, AI Engineers, Machine Learning Engineers, and other specialized technical talent, partnering closely with Engineering leaders to understand their teams, technical requirements, and hiring priorities. You will bring a hands-on sourcing approach, strong technical recruiting judgment, and market intelligence to build exceptional pipelines and deliver high-quality hires. The ideal candidate is an experienced technical recruiter who can independently manage difficult Engineering searches, engage passive technical talent, and advise hiring managers on realistic talent profiles, competitive markets, and effective selection processes. You can speak credibly with engineers about their work and thrive in a fast-paced, evolving technology environment. Key Responsibilities Full-Cycle Technical Recruitment Own searches end to end for Engineering and AI teams, including Senior Software Engineers, AI Engineers, Machine Learning Engineers, and other specialized technical positions. Partner with Engineering hiring managers to translate technical requirements into clear candidate profiles, interview plans, and targeted search strategies. Lead recruiter screens and assess relevant technical experience, project ownership, problem-solving approach, career motivations, and alignment with role requirements. Manage complex searches proactively, identifying bottlenecks, calibrating with interview teams, and keeping high-priority hiring processes moving. Technical Talent Acquisition Strategy Develop search strategies for hard-to-fill technical roles using talent mapping, competitive intelligence, sourcing data, and a deep understanding of Engineering talent markets. Advise Engineering leaders on candidate availability, compensation expectations, market competition, hiring tradeoffs, and realistic recruiting timelines. Work with stakeholders to prioritize openings, align on must-have versus trainable skills, and refine candidate profiles based on market feedback. Use pipeline data, interviewer feedback, and market insights to continuously adjust sourcing and hiring strategies. Technical Sourcing and Candidate Engagement Personally source and engage passive Engineering talent using LinkedIn Recruiter, GitHub, Boolean/X-ray search, technical communities, referrals, networking, and relevant AI-enabled sourcing tools. Build credible relationships with technical candidates by communicating the Engineering challenges, product impact, team environment, and opportunity for growth. Develop and maintain talent pipelines for Software Engineering, AI/ML, and emerging technical skill sets to support current and anticipated hiring needs. Engineering Partnership and Stakeholder Management Build trusted relationships with Engineering leaders, interviewers, HR partners, and other stakeholders to understand organizational goals and evolving technical needs. Provide concise, data-driven updates on search progress, pipeline quality, candidate engagement, interview conversion, and risks to hiring goals. Influence hiring decisions through structured feedback, thoughtful calibration, and a strong candidate and hiring-manager experience. Recruiting Analytics and Process Excellence Track funnel conversion, sourcing channel effectiveness, time to fill, and offer outcomes; translate findings into actions that improve technical hiring results. Partner with Engineering teams to improve interview quality, assessment consistency, candidate communication, and overall process efficiency. Stay current on software engineering, AI/ML hiring trends, recruiting technology, and responsible use of AI tools in sourcing and recruiting workflows. Mentorship Share technical recruiting expertise, sourcing methods, and stakeholder-management practices with other recruiters to elevate team performance. Qualifications Bachelor’s degree in Human Resources, Business Administration, or a related field 5+ years of full-cycle recruiting experience, including significant direct ownership of Software Engineering and other technical searches at the mid-to-senior level. Demonstrated success hiring Senior Software Engineers and related Engineering talent; experience recruiting AI Engineers, Machine Learning Engineers, or similarly specialized roles strongly preferred. Advanced hands-on technical sourcing skills, including Boolean search, LinkedIn Recruiter, GitHub, talent mapping, and proactive outreach to passive candidates. Ability to discuss technical profiles credibly with Engineering leaders, understand common software development and AI/ML concepts, and translate requirements into an effective recruiting strategy. Strong consultative, analytical, communication, and negotiation skills with a track record of managing multiple high-priority technical searches. Work-life, Culture & Perks: Compensation: The base salary range is up to $125K , with flexibility depending on a candidate's background and experience. An annual bonus plan is also included in our compensation package. Well-Being: Medical, dental, vision, short & long-term disability, life insurance and AD&D, and 401k matching. Additional family, wellness, and pet benefits. Home & Family: Paid time off and sick leave, 100% paid parental leave (16 weeks for primary caregivers and 12 weeks for secondary caregivers). We offer a flexible schedule for new parents returning to work. Office Life: Catered lunches, happy hours, pet-friendly spaces, and monthly technology stipend. Growth & Training: $1,000/year for each employee for professional development, as well as opportunities for tuition reimbursement. Sponsorship: We are open to sponsoring candidates currently in the U.S. who need to transfer their active visa. Please check with our Recruiting team if your visa is applicable for transfer. EvolutionIQ / CCC Intelligent Solutions appreciates your interest in our company as a place of employment. We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Location: Remote-Friendly, United States About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is building AI systems that will shape the trajectory of one of the most consequential technologies in human history. That work requires physical infrastructure at significant scale, and building that infrastructure the right way means being a real, long-term partner to the communities where we operate. We are looking for a Community Engagement Manager in Indiana and Kentucky to join our Public Policy team and serve as Anthropic's on-the-ground presence in the communities where our data centers are sited, built, and operated. This is not a communications role or a government affairs role, though you will do elements of both. It is a relationship role: your job is to make Anthropic a trusted, visible, and valued neighbor, from the earliest stages of site selection through construction and long-term operations. You will be the connective tissue between Anthropic's Policy and Infrastructure teams and the local officials, community organizations, economic development partners, and residents who have a stake in what we build. You will surface concerns before they escalate, translate our technical and operational plans into clear local benefits, and build the coalitions that allow us to move quickly and responsibly. Because Anthropic's infrastructure footprint is still early in its growth, you will also help write the playbook: the processes you build in your first markets are the ones we will use as we expand. You will travel regularly within Indiana and Kentucky, up to 50% of the time, and occasionally to other Anthropic data center markets. Key responsibilities Build and maintain trusted, sustained relationships with county commissioners and councils, Kentucky fiscal courts and judge-executives, mayors and city councils, plan commissions and zoning boards, state and regional economic development organizations, community groups, civic leaders, educational institutions, and workforce partners in the Indiana and Kentucky data center markets you cover Develop and execute a community engagement strategy for each of your markets, spanning site selection, pre-development, construction, and ongoing operations Build external coalitions, host education and listening sessions, and design local solutions that deliver real benefits to the communities where we operate Represent Anthropic in public forums, town halls, planning hearings, community events, and local media Monitor community sentiment and local political dynamics, and advise internal teams on risks, opportunities, and the right pace and posture for engagement Partner with the Real Estate and Infrastructure team to bring community input into how projects are planned, communicated, and delivered, not just how they are announced Work with the Communications team to develop proactive, locally relevant messaging Coordinate charitable giving, community investment, and economic development commitments in your markets, including managing nonprofit partner relationships Partner with the Energy and Sustainability team to explain our approach to environmental stewardship and respond to questions about power, water, and land use, including how large electricity needs are served by local utilities and rural electric cooperatives Build a community engagement playbook and repeatable processes that scale as Anthropic's infrastructure footprint grows Minimum qualifications Experience in community affairs, public affairs, economic development, government relations, local or state government, or a closely related field Direct experience working for or engaging with county and municipal governments and a broad set of community stakeholders on behalf of large infrastructure, construction, energy, or technology projects, with a working understanding of how local politics and community dynamics actually play out A skilled relationship and coalition builder who earns trust with a diverse group of stakeholders, and who maintains relationships through difficult conversations The ability to represent a company credibly in public settings, including town halls, hearings, and press interviews Strong written and verbal communication skills, including the ability to turn a complex operational plan into plain language that a local official or reporter can understand and respond to The ability to work independently, get up to speed quickly on complex policy issues, and manage multiple concurrent engagements across different markets without losing track of any of them Based in Indiana or Kentucky or willing to relocate to one of them, and prepared to travel regularly across both states Preferred qualifications 7+ years of experience in community engagement specifically on data center, utility, energy, or large-scale industrial infrastructure projects, or in local government Familiarity with land use, zoning, and permitting processes at the county and municipal level in Indiana and/or Kentucky, including local tax abatement and incentive approvals Experience managing corporate social responsibility programs Established relationships with economic development, workforce, or civic organizations in the markets this role covers Experience working with real estate, legal, communications, and policy teams at the same time A genuine interest in the communities where you work, not just the projects you are managing The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $265,000 — $295,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: London Workplace: Hybrid ABOUT BEAMERY With the rapid expansion of AI and automation, the future of work has never been more challenging for organizations. Beamery’s unique jobs, skills and tasks data platform helps organizations navigate these challenges and make more informed decisions across Talent Lifecycle Management. Our solutions power recruitment, mobility, upskilling, diversity, work architecture and workforce planning for some of the world’s most forward-thinking companies. We believe that where you work is much more than just a job. Millions of people are being left behind every day in their careers, and we’re on a mission to fix this by creating equal access to meaningful work, skills and careers for all. We are an equal opportunity employer committed to building a representative Beamery, creating an equitable, inclusive and engaging environment for our people. So, what are you waiting for? Join us and help us transform the future of work once and for all. What’s ahead — and why it’s an exciting time to join the team:  Building agentic AI with advanced orchestration (multi-agent workflows, tool use, evaluation loops) that turns complex talent data into decisions. - Training and fine-tuning our own models on unique data about jobs, skills and tasks, and benchmarking them against the best in our market. - Joining an award-winning AI team (ACM RecSys Challenge 2026) that turns new ideas into innovative solutions with scientific rigour. - Sharing our work and learning from industry peers through challenges, conferences and publications. But it’s not all about creating high-quality products, we also very much value the company culture we have worked hard to create; built on trust, empathy & honesty ensuring our workforce is able to bring their full selves to work. ABOUT THE TEAM The Data Science team builds the AI models behind Beamery's Data Foundry, the common data and AI layer powering all Beamery products, and works hand in hand with the product teams to empower their features with AI (such as Talent Match and recommendations). At the heart of our work is the Beamery taxonomy, the language of work (skills, role titles and tasks) that every Beamery product speaks, built on more than a decade of research and kept current by the Taxonomist, our agentic system, so it reflects the real pulse of the job market. We combine LLMs, Transformers and embedding models with classic machine learning, always choosing the best balance between quality, latency and cost. We see ourselves as pioneers in AI for HR Tech: in 2026 the team finished 1st in the industry track and 2nd overall out of 40 teams at the ACM RecSys Challenge. ABOUT THE ROLE You will join the team as a Senior Data Scientist and own our matching, recommendation and taxonomy mapping models, working closely with the product engineering teams that bring them to our customers. You will be responsible for the full cycle of your work, from defining how quality is measured and designing the models to running robust scientific experiments, tracking technical and business metrics, and writing and reviewing code. You will also advise the product teams on how to implement AI features with an evaluation-first mindset, and keep pushing the boundaries of Beamery's AI. KEY RESPONSIBILITIES - Build, improve and own our matching and recommendation models (e.g. candidate to job matching, internal mobility recommendations etc.). - Apply an evaluation-first mindset: build golden datasets from real recruiter and user decisions, define quality metrics, design and run robust scientific experiments, track and report both technical and business metrics (using LLM-as-a-judge and human feedback), and communicate results and metrics clearly to the product teams. - Write clean and tested Python code using AI coding agents (such as Claude Code or Codex), and review code with care, both from your peers and from AI agents, so the team's codebase stays consistent, readable and safe. - Follow recent research (e.g. LLMs, embeddings, recommender systems, explainability, model evaluation) and bring the most relevant ideas into our product roadmap. - Document your work and present it clearly to product, engineering and business stakeholders, and contribute to the team's research visibility (such as challenges, conferences and publications). REQUIRED SKILLS AND EXPERIENCE - A minimum of 2-4 years of experience as a Data Scientist, Senior Data Scientist (or a similar role) in an AI startup or an AI team, with a dynamic environment and a variety of use cases. - Strong experience with recommender systems, search, ranking or matching (e.g. learning-to-rank, scoring models, Gradient Boosting Trees, embedding models). - Fluency in evaluation: designing datasets and quality metrics (such as AUC, NDCG, precision and recall), and using LLM-as-a-judge and human feedback. - A strong foundation in NLP and GenAI, including Transformers, LLMs and embedding models (training or fine-tuning them is a strong plus). - High-quality software development skills in Python (clean design, testing, packaging, maintainable code etc.), practical knowledge of CI/CD, and hands-on experience with agentic coding, with the judgement to know when AI-generated code is right or wrong. - The ability to simplify complex problems, to work with ambiguity, and to collaborate with data scientists, engineers, product managers and business stakeholders. - A Master's degree or PhD, or equivalent experience, in Computer Science, Data Science, Mathematics or a related field. NICE TO HAVE - Experience with explainable or conversational recommendations. - Experience in HR Tech, talent acquisition or workforce data. - Publications, open-source contributions or strong results in ML challenges (e.g. RecSys, Kaggle). WHAT WE OFFER - The chance to own core AI models that are used by some of the world's most forward-thinking organisations. - A team that publishes, competes and is recognised in the research community, while shipping real products. - Work with the latest AI technologies and tools, including AI coding agents as part of the daily workflow. - Close collaboration with experienced data scientists, QA, platform and product engineers. At this time, we are unable to provide Visa sponsorship for this role. Beamery is for Everybody. Diversity and open expression are fundamental to us. We acknowledge the challenges in our industry and strive to develop an inclusive culture where everybody can contribute. We are dedicated to creating an inclusive environment for everyone, regardless of ethnicity, religion, color, sexual orientation, gender identity, race, national origin, age, disability status, or caregiver status. If, for whatever reason, you need us to make reasonable adjustments and adaptations to our recruitment process, please email accommodations@beamery.com Visit our Diversity, Equality and Inclusion page https://careers.beamery.com/life-at-beamery/diversity-equality-inclusion/to learn more about progress and commitments.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Utilization improvements are worth enormous sums at our scale. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at exabyte scale. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.