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Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking an iOS Software Engineer to build and enhance its AI-native mobile experience. This role is responsible for developing production-grade iOS applications where AI interactions are central to the user experience, ensuring performance, reliability, and user trust across all mobile interactions. Working closely with backend and machine learning teams, this position will focus on delivering scalable iOS applications that integrate advanced AI capabilities while maintaining a seamless and intuitive user experience. Key Responsibilities Build and maintain production iOS applications using Swift and SwiftUI . Integrate AI-powered features through backend APIs. Design user experiences for AI interactions, including loading states, streaming responses, retries, and fallback mechanisms. Optimize application performance, memory usage, and battery efficiency. Implement user feedback and analytics mechanisms to support AI evaluation and continuous product improvement. Collaborate closely with backend and machine learning engineers on API design and system behavior. Maintain high standards of application quality, stability, and reliability for App Store releases. Requirements Minimum 3 years of iOS development experience using Swift. Hands-on experience integrating AI-powered features into mobile applications. Strong understanding of async/await , concurrency, and background task management. Solid experience optimizing iOS application performance, memory usage, and responsiveness. Experience developing, releasing, and maintaining production iOS applications. Familiarity with designing applications that operate reliably under latency, partial failures, and non-deterministic AI behavior. Exposure to CoreML or lightweight on-device machine learning is an advantage. Familiarity with feature flags or remote configuration systems is preferred. Strong understanding of user experience design for AI-powered applications, with an emphasis on usability and user trust. Preferred Technical Skills Experience with the following technologies is preferred: Swift SwiftUI Swift Package Manager (SPM) SQL and NoSQL databases TensorFlow Lite (on-device inference)

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is looking for a Full Stack Engineer – AI Systems to build AI-native product experiences that transform advanced AI capabilities into intuitive, production-ready workflows. This role combines frontend, backend, and AI engineering to develop intelligent features that are reliable, scalable, and user-centric. Working closely with product, backend, and machine learning teams, this position will focus on designing end-to-end AI workflows, integrating large language models (LLMs), and delivering seamless user experiences across web applications. Key Responsibilities Build end-to-end product features across frontend, backend, and AI integrations. Design and develop AI agent workflows that support planning, tool usage, failure handling, and recovery across multiple steps. Integrate LLMs, memory systems, and external tools into scalable, production-grade applications. Design responsive AI interactions with streaming capabilities, partial results, and low-latency performance. Improve system reliability, observability, and fallback mechanisms for AI-powered features. Collaborate closely with product, backend, and machine learning teams to deliver features from concept to production. Continuously iterate and improve product functionality based on user feedback, production insights, and real-world usage. Requirements Strong experience in full stack software engineering across frontend and backend development. Solid understanding of system design, scalable architecture, and API development. Experience building AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or similar technologies. Ability to work effectively in fast-paced environments with evolving requirements. Strong ownership mindset with experience delivering features from ideation through production deployment. Excellent problem-solving skills and the ability to make pragmatic engineering decisions in ambiguous situations. Preferred Technical Skills Experience with some or all of the following technologies is preferred: Next.js Python Node.js PyTorch OpenAI, Anthropic, or open-source Large Language Models (LLMs) SQL and NoSQL databases Kubernetes Docker

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking an Android Software Engineer to build and enhance its AI-native mobile experience. This role is responsible for developing production-grade Android applications where AI is at the core of the user experience, ensuring performance, reliability, and usability across all mobile interactions. Working closely with backend and machine learning teams, this position will focus on delivering scalable Android applications that integrate advanced AI capabilities while maintaining a seamless user experience. Key Responsibilities Build and maintain production Android applications using Kotlin . Integrate AI-powered features such as chat, vision, voice, and recommendation systems through backend APIs. Design intuitive user experiences for AI interactions, including streaming responses, retries, and partial results. Optimize application performance, memory usage, and responsiveness for AI-intensive workflows. Implement analytics, logging, and user feedback mechanisms to support continuous AI evaluation and product improvement. Collaborate closely with backend and machine learning engineers to define API integrations and system behavior. Ensure application stability, security, and scalability within production environments. Requirements Minimum 3 years of Android application development experience using Kotlin. Hands-on experience integrating AI-powered features, such as Large Language Models (LLMs), computer vision, or speech APIs. Strong understanding of asynchronous programming using Coroutines and Flow . Experience working with RESTful or gRPC APIs and structured data formats. Strong debugging, troubleshooting, and performance profiling skills. Experience developing applications that operate reliably under conditions involving latency, partial failures, and non-deterministic behavior. Familiarity with ML Kit or lightweight on-device inference is an advantage. Experience publishing and maintaining production applications on the Google Play Store . Preferred Technical Skills Experience with the following technologies is preferred: Kotlin / Java SQL and NoSQL databases TensorFlow Lite (on-device inference)

Location: Tabuk, Saudi Arabia; Jeddah, Saudi Arabia; Riyadh, Saudi Arabia; Yanbu, Saudi Arabia The Operations Engineer will be responsible for monitoring and controlling the operation of all facility systems and coordinating maintenance-related activities at the Primary Nursery Facility in NEOM. The role will also oversee the delivery of support services, including Janitorial, Horticulture, Pest Control, Waste Management, and Office Services. The Operations Engineer will ensure the safe, efficient, and reliable operation of electro-mechanical systems, monitor service provider performance, ensure compliance with operational KPIs, resolve customer complaints, and continuously identify opportunities to improve facility performance, energy efficiency, and end-user satisfaction. Key Responsibilities Supervise and coordinate the daily operation of all MEP and electro-mechanical systems at the Primary Nursery Facility. Monitor and control equipment including MCCs, pumps, VFDs, fans, instrumentation, emergency generators, AHUs, chillers, and related systems. Plan operational activities, establish priorities, and coordinate maintenance and project-related works. Conduct regular inspections and monitor system performance to ensure facility readiness, reliability, and compliance with operational requirements. Analyze system performance, operating parameters, alarms, and set points, and implement corrective actions and improvement initiatives. Respond promptly to emergencies, major faults, equipment failures, and operational interruptions. Support Root Cause Analysis (RCA), incident investigations, commissioning activities, and the implementation of corrective actions. Manage and monitor contractors and service providers delivering Janitorial, Horticulture, Pest Control, Waste Management, and Office Services. Ensure customer satisfaction by resolving complaints, high-priority tickets, and recurring operational issues while monitoring service delivery against KPIs. Requirements Bachelor’s degree in Electrical, Mechanical, Electro-Mechanical Engineering, or a related field. 4–6 years of experience in Facility Management, Facility Operations, or a similar role. Proven experience in the operation and monitoring of MEP and electro-mechanical systems. Good knowledge of facility systems and equipment, including MCCs, pumps, VFDs, generators, AHUs, chillers, fans, and instrumentation. Ability to read and interpret technical drawings and understand MEP commissioning procedures. Experience in contractor management, service provider coordination, and KPI monitoring. Strong knowledge of troubleshooting, problem-solving, Root Cause Analysis (RCA), and corrective action processes. Good communication, leadership, coordination, analytical, and customer service skills. Good command of written and spoken English, with the ability to work effectively under pressure and respond to operational emergencies.

Location: San Francisco Workplace: OnSite 🧠 ABOUT LEGION HEALTH At Legion Health https://legionhealth.com, we believe everyone deserves fast, affordable, and world-class health care, and we’re developing the AI infrastructure to deliver it ourselves at world scale. Legion is building autonomous medical care (the AI doctor), starting with psychiatry. Our AI-native care-delivery platform currently automates 95% of the administrative work required for us to deliver direct patient care. We also recently became the first company ever to receive regulatory authorization to let AI prescribe psychiatric medications https://nypost.com/2026/03/27/business/artificial-intelligence-can-now-prescribe-mental-health-drugs/, allowing us to not only collapse health care’s admin costs but also its clinical labor costs—shifting this industry’s economics from humans to tokens. Our technical moat is hard to copy—we combine rich data, production AI, doctors in the loop, and end-to-end care operations to deliver measurably better care to a clinically complex patient population. This has helped us produce tens of thousands of total visits in just 2 years, all while holding ops costs flat and achieving industry-leading patient NPS and retention. While the last generation of healthcare startups made the existing system incrementally more efficient, Legion is rebuilding full-stack care delivery from first principles. Our vision? A 10X better patient experience that’s higher quality, less expensive, and more scalable than ever before. And a 10X better clinician experience that frees our providers to focus on what matters most: caring for patients. Legion Health is backed by Y Combinator, leading venture capital firms, and founders from Function Health, Modern Health, Everly Health, Trusted Health, Clipboard Health, PatientPing, Sesame Care, Faire, EasyPost, and fuboTV. Join us as we build the future of health care: faster, higher-quality, and more affordable, powered by doctors and AI working together. 📍 ROLE LOGISTICS - Job Type: Full-Time - Role Type: GTM Engineering / Revenue Systems / Provider Partnerships / AI Automation / Data & Attribution - Ideal Experience Level: 5+ years, including 3+ years owning GTM systems, revenue automation, growth engineering, or technical RevOps - Location: In-Person in San Francisco, CA - US Visa Sponsorship: Yes 🚀 THE OPPORTUNITY Legion is hiring a GTM Engineer to build the AI-native commercial and referral infrastructure behind our provider-partnership motion. Your systems will help us identify the right provider organizations, reach the right stakeholders, turn interest into referrals, and move referred patients into care quickly. This is not a traditional RevOps or CRM administration job. You will own the technical architecture from market mapping and outbound through referral intake, attribution, eligibility, onboarding, and partner reporting. You will configure best-in-class tools when they are sufficient and write code or build integrations, agents, and internal products when they are not. You will build both sides of our sales motion. From the bottom up, Legion needs a complete view of every clinic, location, physician, referral coordinator, and office leader in a market. From the top down, we need to map enterprise medical groups, centralized referral teams, executives, clinical leaders, and every stakeholder who can shape a partnership. The system should tell each representative who matters, why they matter, what happened last, and what to do next. You will also engineer the path from referral to care. Referrals may arrive through fax, forms, APIs, tracked links, QR codes, phone calls, or patients who begin online after a provider recommendation. Regardless of channel, Legion must identify the source, resolve the provider and organization, preserve attribution, process the referral, initiate eligibility and onboarding, and synchronize the right data across our CRM, product, analytics, and patient-engagement systems. The right person is a hands-on systems builder with strong product judgment. You should be comfortable choosing a CRM, modeling complex account hierarchies, writing SQL and lightweight production code, integrating APIs, deploying AI workflows, debugging failures, and partnering with sales, product, engineering, data, operations, clinical, compliance, and security teams. Over time, you will help turn provider partnerships into a secure product that makes Legion the easiest specialty care partner in the country: simple to refer patients to, easy to collaborate with, and consistently responsive. ✅ RESPONSIBILITIES AND DELIVERABLES - Select and architect Legion’s provider-partnership CRM—whether HubSpot, Salesforce, Attio, or another AI-native platform—as the source of truth for organizations, locations, stakeholders, opportunities, referrals, ownership, and next actions. - Design a durable account hierarchy that connects individual clinicians, clinic locations, care teams, medical groups, parent organizations, enterprise partnerships, and internal owners without losing history or context. - Build a provider prospecting data layer using NPI and claims data, Definitive Healthcare or similar datasets, public sources, enrichment providers, and Legion’s internal data. - Create account-scoring and territory systems that prioritize targets using geography, specialty, patient volume, payer mix, referral potential, network relationships, and engagement signals. - Build coordinated outbound workflows across email, phone, LinkedIn, direct mail, events, lunch-and-learns, and field sales using tools such as Clay, Apollo, LinkedIn Sales Navigator, sequencing platforms, AI agents, and custom integrations. - Map clinic-level champions and referral coordinators alongside enterprise executives, clinical leaders, operations leaders, and centralized referral teams so Legion can sell from the bottom up and the top down. - Equip sales representatives with accurate contact data, office addresses, account briefs, relationship history, meeting preparation, follow-up automation, and clear next-best actions. - Deploy AI-assisted workflows for account research, stakeholder discovery, enrichment, outreach drafting, call intelligence, CRM updates, and follow-up with appropriate evaluations and human review. - Build an omnichannel referral-ingestion layer that turns fax, forms, APIs, tracked links, QR codes, phone calls, provider handoffs, and patients who begin online after a provider recommendation into structured, traceable records. - Automate referral processing, including document extraction, provider and organization matching, deduplication, completeness checks, routing, exception handling, and audit trails. - Connect referral intake to insurance eligibility and AI-native front-desk workflows for patient outreach, onboarding, and scheduling so referred patients reach the right next step without avoidable delays. - Own end-to-end attribution across the referring clinician, clinic, parent organization, partnership, sales representative, campaign, channel, UTM, QR code, landing page, fax source, and downstream patient journey. - Integrate the provider CRM, Legion’s database, the patient-facing CRM, PostHog, Braze or another lifecycle platform, analytics systems, and custom applications into one coherent data flow. - Partner with product and engineering to build secure provider-facing dashboards and workflows for referral volume, referral status, time-to-contact, scheduling progress, coverage and copay information, and other authorized care-coordination information. - Build compliant workflows that return medical records, care summaries, and status updates to referring care teams through approved fax, secure email, portal, interoperability, or other authorized channels at the right cadence. - Create dashboards and operating reviews for market coverage, stakeholder penetration, outreach performance, pipeline, referral volume, conversion, speed to care, repeat referrals, partner expansion, and revenue impact. - Own production reliability across monitoring, logging, retries, rate-limit handling, identity resolution, testing, versioning, access control, documentation, and recovery when systems fail. - Treat HIPAA, PHI handling, minimum-necessary access, role-based permissions, audit trails, consent, and provider trust as product requirements in every automated workflow. - Make disciplined build-versus-buy decisions, ship useful first versions quickly, and drive adoption through clear playbooks, training, and change management. 🏆 YOU’LL BE SUCCESSFUL IF YOU… - Give Legion a provider CRM and data model that the team trusts as the source of truth. - Create a complete, prioritized map of each market so representatives spend time with the right organizations and people. - Build a repeatable outbound engine that produces qualified provider conversations and pipeline through coordinated digital, field, bottom-up, and top-down plays. - Ensure every referral is captured, processed, routed, and attributed correctly regardless of how it arrives. - Reduce the time from referral to eligibility, patient contact, onboarding, scheduling, and completed care. - Give referring care teams a secure, useful experience that increases trust and repeat referrals. - Remove repetitive research, data entry, document processing, routing, follow-up, and reporting work without sacrificing accuracy or judgment. - Build reliable systems that sales and operations adopt, improve continuously, and measurably increase referral volume, conversion, speed to care, partner retention, and revenue. 🧰 IDEAL BACKGROUND AND SKILLS - 5+ years in GTM engineering, revenue operations, sales operations, growth engineering, business systems, data engineering, internal tools, or another systems-building role close to revenue. - 3+ years directly owning CRM architecture, GTM automation, data pipelines, outbound infrastructure, attribution, or technically complex revenue programs. - Strong technical foundation: advanced SQL plus the ability to write and review production-quality Python, JavaScript, or TypeScript for integrations, automations, and internal tools. - Deep CRM fluency in HubSpot, Salesforce, Attio, or similar, including objects, associations, account hierarchies, lifecycle stages, permissions, routing, reporting, deduplication, and data governance. - Hands-on experience with APIs, webhooks, ETL or reverse ETL, event instrumentation, identity resolution, error handling, observability, and modern data warehouses. - Practical fluency with modern GTM tools such as Clay, Apollo, Definitive Healthcare, LinkedIn Sales Navigator, Outreach, Salesloft, n8n, Make, Zapier, Workato, or equivalent platforms. - Production experience with LLM-powered research, extraction, classification, routing, or agentic automation, including structured outputs, evaluations, monitoring, confidence thresholds, and human-in-the-loop review. - Strong analytical judgment across funnels, attribution, pipeline, conversion, velocity, cohort analysis, experimentation, and revenue impact. - Strong product sense and build-versus-buy judgment. You can turn a messy frontline problem into a coherent system that people trust and use. - Strong preference for experience in healthcare, provider partnerships, referrals, physician networks, field sales, multi-location organizations, or another complex relationship-driven business. - Healthcare and security judgment: disciplined access controls, auditability, minimum-necessary access and data use, consent, and close partnership with compliance and clinical leaders. - Bonus: experience with eFax, referral management, EHR integrations, HL7, FHIR, eligibility, claims, provider directories, or NPI data. - Excellent cross-functional communication. You can translate the needs of a sales representative, referral coordinator, operator, clinician, engineer, analyst, and executive into a system that works. - Low ego, high ownership, and startup intensity. You can diagnose the bottleneck, design the solution, ship a useful version, measure the result, and improve it quickly. 💰 COMPENSATION & BENEFITS - Salary: $140,000 – $260,000, based on experience - Early-Stage Equity: Meaningful ownership in a category-defining company. - Health Insurance: Medical, dental, and vision benefits - Additional Perks: In-person retreats, meal stipends, GTM and revenue-systems tooling budget, learning stipend, AI tooling budget - Time Off: Flexible, unlimited vacation policy - Work Hours: Flexible, with responsiveness around high-impact launches or system issues - Work Setup: In-Person in San Francisco, CA - Impact: Build the technical system that turns partnerships into faster access to high-quality medical care for all. - Autonomy and Learning: Own CRM architecture, provider data, outbound infrastructure, referral workflows, attribution, AI automation, reporting, and partner-facing systems end-to-end. - Growth Opportunities: As Legion scales, this role can grow into Head of GTM Engineering, Head of Revenue Operations, or a broader product and growth leadership role. 📝 HOW TO APPLY AND HIRING PROCESS - Apply here: https://jobs.ashbyhq.com/legionhealth/3a007cb1-faad-4854-a847-e4b77eaf3a42 - Overview of our hiring process: 1. Resume + Application Screen 2. Founder Interview 3. GTM + AI Systems Deep Dive 4. Professional Reference Checks - Estimated time-to-hire: 2 weeks - Start date: ASAP - Hiring manager: Arthur MacWaters 🤝 EQUAL EMPLOYMENT OPPORTUNITY Legion Health is proud to be an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, contractors, and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, genetic information, or any other protected characteristic under applicable law. We encourage applicants from all backgrounds to apply.

Location: 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 Code RL at Anthropic drives reinforcement learning efforts behind Claude's coding capabilities, creating and scaling agentic coding environments. This is an engineering role with unusual latitude to set technical direction and standards. You'll be part of a team solving the engineering side of research efforts such as embedding with research teams, getting up to speed on their systems and needs, and designing the frameworks, APIs, and infrastructure that let researchers move faster, then rotating off, leaving behind well-oiled systems those teams can understand, own, and maintain themselves. Your remit also includes the ongoing health of production RL runs: maintainable, monitored, and straightforward to triage. The team's problem space spans the client side of sandboxed execution for agentic RL environments, large-scale data processing jobs, the lifecycle of production datasets, and the frameworks researchers build environments on. You won't own all of this yourself, you'll take on the slices where your depth matters most. You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and hard-won intuition for how complex systems fail — especially silently. You should be comfortable diving into messy research code, finding the load-bearing abstractions, and improving them incrementally while researchers continue to build on top of your work. Key responsibilities Design widely-used APIs, frameworks, and abstractions that other engineers and researchers build on, with careful attention to interface legibility and principled defaults Embed with research teams on a rotational basis: understand their engineering needs, build systems and APIs that support their work, and transfer ownership so teams can maintain those systems after you rotate off Work directly in research codebases, improving reliability and structure without slowing down the research they support Anticipate silent failure modes and prevent them structurally through type safety, well-designed invariants, targeted testing, and refactors that shrink the surface area for bugs Contribute to the reliability of production RL systems, including monitoring, regression detection, and triage tooling Help define engineering standards, review practices, and design patterns for a new team, and mentor researchers and engineers in adopting them Minimum qualifications Deep expertise in Python, including static typing, safe async and concurrency patterns, and writing performant Python code A track record of designing intuitive, safe APIs or frameworks that other engineers or teams adopted and built on Experience working productively in large, evolving, or research-style codebases that you didn't originally write Demonstrated ability to anticipate failure modes — especially silent ones — and prevent them structurally through system design, type safety, and testing Strong written and verbal communication skills, including the ability to explain system designs to collaborators with varied engineering backgrounds Comfort with ambiguity: able to scope your own work from a loosely defined problem and drive it to a maintainable outcome Preferred qualifications Experience building infrastructure, tooling, or frameworks for machine learning research or RL workflows Familiarity with reinforcement learning concepts, agentic systems, or LLM training pipelines Experience building or operating large-scale distributed systems Experience building client libraries or SDKs on top of sandboxed, containerized, or remote execution platforms Experience with large-scale data processing or dataset lifecycle management Experience designing plugin systems or extensible class hierarchies used across an organization Experience embedding with or consulting for other teams, including successfully handing off systems for others to own Experience defining code standards, lint rules, or static verification approaches adopted across multiple teams Prior experience as a technical lead, or setting engineering standards for a team Prior experience maintaining an open source project Representative projects These are examples of the challenges the team tackles; no one person will work on all of them: Design a base RL environment abstraction general enough to be subclassed across a wide range of environments Design a model-tool interface for sandboxed agentic environments that has explicit serialization semantics Partner with the platform teams that own the sandbox runtime to specify low-level features that improve the integrity of agentic coding tasks Design probes that catch sandbox regressions early Design the lifecycle and maintenance scheme for a production dataset Lead a research code refactor replacing loosely structured data containers with equivalents that carry stronger correctness guarantees, without breaking the experiments that depend on them Design lint rules and code-style requirements that favor statically verifiable patterns — including patterns less likely to be overlooked by an LLM reviewing or writing the code — to shrink the surface area for silent bugs Build the access layer that lets researchers discover and reuse data artifacts across teams 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 — $625,000 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: San Francisco, CA | 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's Environments organization builds and maintains the infrastructure that improves Claude’s capabilities through reinforcement learning. That includes the frameworks researchers use to build environments and the infrastructure responsible for running them. The team's mission is to productionize research. You'll embed with research teams, get up to speed on how they work, and design the frameworks and APIs that let them move faster, building systems the team can understand, own, and maintain themselves. Scope also includes keeping production RL runs healthy, maintainable, monitored, and easy to triage. You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and good intuition for how complex systems fail, especially silently. It's a bonus if you've built and operated a stateful distributed system, such as a workflow engine, actor framework, or durable-execution runtime, where correctness depends on getting shared state and recovery right. You should be comfortable diving into messy research code, finding the abstractions that matter, and improving them incrementally while researchers continue to build on your work. You should also be comfortable using AI tools to accelerate your own development, but have an impulse towards deep verification. Key responsibilities Design widely used APIs, frameworks, and abstractions that other engineers and researchers build on, making correct usage the default and ruling out entire classes of errors structurally Own the platform layers that sit beneath every environment, including the agent runtime Build the tooling that lets environment owners understand, debug, and maintain their environments in production without needing an infrastructure engineer in the loop Embed with research teams on a rotational basis, work directly in their codebases without slowing down the research they support, and transfer ownership when you rotate off Anticipate silent failure modes and prevent them structurally through type safety, well-designed invariants, targeted testing, and refactors that reduce the room for correctness issues Drive adoption of new frameworks across the organization, including deprecations and cutovers Help define the engineering standards, review practices, and design patterns for a new team, and mentor researchers and engineers in adopting them Minimum qualifications Deep expertise in Python, including static typing, safe async and concurrency patterns, and writing performant code Strong taste in API and framework design, the ability to explain why an interface is right or wrong rather than just recognizing it, and a track record of other engineers or teams adopting and building on frameworks you have built Experience designing or operating stateful concurrent or distributed systems, and reasoning carefully about failure, retries, idempotency, and consistency A habit of verification: you measure before you conclude, and you build the checks that let a system show it's correct Experience working productively in large, evolving, or research-style codebases that you didn't originally write Strong written and verbal communication with collaborators of varied engineering backgrounds, and comfort with ambiguity: able to scope your own work from a loosely defined problem and drive it to a maintainable outcome Preferred qualifications Experience building infrastructure, tooling, or frameworks for machine learning research or RL workflows, and familiarity with agentic systems or LLM training pipelines Experience building agent frameworks, orchestration engines, or multi-agent systems, including checkpoint and restore, replay, and coordination of long-running stateful processes Experience using AI coding tools on code where correctness matters, with good judgment about what to delegate and how to make the results verifiable Experience building client libraries or SDKs on top of sandboxed, containerized, or remote execution platforms Experience with large-scale data processing, dataset lifecycle management, or data lineage systems Experience designing serialization schemes, plugin systems, or extensible class hierarchies used across an organization Experience embedding with or consulting for other teams and handing off systems for others to own, or defining code standards adopted across teams, or prior experience as a technical lead Representative projects These are examples of the challenges the team tackles: Design a base RL environment abstraction that can be subclassed to support the large majority of environments built across RL Redesign the model-tool interface for sandboxed agentic environments so that state is guaranteed to survive serialization, making it structurally impossible to write a tool that silently loses state Design the state-sharing and recovery model for multi-agent workloads, so that losing a sandbox partway through a task becomes a transparent resume rather than lost work Define the failure and retry model for a sandboxed execution platform, distinguishing infrastructure faults from genuine task outcomes so that each is handled correctly Build the tooling that lets an environment owner diagnose why their environment is unhealthy in a production run, and fix it themselves 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 — $605,000 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: Canada; Calgary; Winnipeg; Vancouver; Halifax; Edmonton; Toronto; Victoria; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We are on a mission to build machines that understand the world and make them safely accessible to all. Data quality is foundational to this process. Machines (or Large Language Models, to be exact) learn in similar ways to humans, by way of feedback. By labelling, ranking, auditing, and correcting model output, you will improve Large Language Models' performance for iterations to come, thus having a lasting impact on Cohere's technology. We are hiring Generalist professionals with broad backgrounds that span multiple consumer-facing or personal domains. This is a judgment-driven role, not passive data entry. You will review, assess, and provide structured feedback across a broad and evolving range of tasks, evaluating, stress-testing, and improving our models on English-language data spanning multiple modalities (text, image, and structured formats such as JSON, CSV/TSV, and Markdown). This is a great opportunity for professionals with strong analytical skills to contribute to high-impact annotation projects. Please Note: This is a part-time independent contractor position available within Canada only. We seek candidates who can commit to 16 hours per week at a CAD $30/hour contract rate. This role is BYOD 💻 (Bring Your Own Device, laptop). This position is remote. As an Data Annotation Specialist, you will: - Evaluate and rank model outputs: Complete preference and comparison tasks, assessing which responses best conform to project guidelines for accuracy, helpfulness, tone, and safety, and writing clear justifications for your judgments. - Stress-test and break models: Probe models adversarially to surface failure modes, unsafe behavior, and capability gaps, and document reproducible cases that engineering and research teams can act on. - Create datasets: Author high-quality prompts, responses, and exemplars to build training and evaluation datasets, following detailed specifications and editing machine-written or human-written outputs to standard. - Build and apply rubrics and taxonomies: Contribute to the design of grading criteria and rubrics, then apply them consistently to produce structured, high-quality annotations across task types. - Annotate and correct multimodal data: Label, audit, and rectify inaccuracies across text, image, and structured data, maintaining a high standard of data integrity and accuracy. - Calibrate and maintain consistency: Participate in calibration exercises and inter-annotator agreement checks to align on standards, and flag ambiguous or uncovered edge cases rather than guessing, since a single misjudgment replicated at scale degrades a model. - Adapt to experimental work: Take on new and evolving task types as project needs shift, applying sound judgment in areas where guidelines are still being developed. - Report on model performance: Surface and communicate quality and performance trends in model and agent behavior, giving cross-functional partners clear, well-evidenced feedback on where models succeed, fail, and degrade. You may be a good fit if you have: - 1+ years of experience in AI data annotation, LLM evaluation, content moderation, research, or a related analytical role, with exposure to quality assurance, and/or preference ranking. - Experience applying detailed guidelines to complex and often ambiguous content, with strong contextual and sociocultural judgment, sensitivity to nuance, tone, and register, and the ability to reason well in cases where there is no single correct answer. - Comfort with ambiguity: a willingness to flag unclear or uncovered edge cases rather than guess, and to work productively on novel, experimental tasks whose definitions are still evolving. - A sharp, curious eye for inconsistencies, subtle errors, and model failure modes, including the instinct to probe models adversarially and surface where they break. Familiarity with how large language models behave, such as hallucination, sycophancy, and instruction-following gaps, is a plus. - Excellent command of written English and strong reading comprehension, with the ability to clearly justify your evaluations, including why an output is correct or incorrect, high-quality or low-quality, and to write clear prompts and exemplars that explain your reasoning. Bonus points if you are fluent in another language! - Strong attention to detail and commitment to accuracy, with the ability to maintain consistency across high-volume and monotonous tasks. - Comfort working with annotation platforms and structured formats such as JSON, CSV/TSV, Markdown, XML, and YAML. - Strong execution in a remote environment, including good time management, comfort using new tools, and the ability to work independently in a global, asynchronous team. Candidate Journey - Initial Screening: Our Talent Team will review your application. - First Assessment: If selected to move forward, you’ll receive a multiple-choice assessment by email. - Second Assessment: Candidates who achieve a passing score will be contacted by a member of our team to complete a more comprehensive assessment focused on their area of expertise. - Video Screen: If selected to move forward, you’ll have a short video call with a member of our Operations Team. - Final: Selected candidates will receive an Independent Contractor Agreement. As an independent contractor, you maintain control over how you complete your work and may work with multiple clients simultaneously, although we ask you to declare if any of these are with a direct competitor of Cohere and maintain IP confidentiality of the Cohere project. Independent contractors are not eligible for health benefits or other benefits provided to employees. Compensation for services is provided to contractors by contractors invoicing for services provided pursuant to the terms of our agreement with the contractor. It is important to understand that as an independent contractor, continuous work is not guaranteed. The client-contractor relationship is fundamentally project-based, meaning engagements may be temporary, periodic, or intermittent based on our organizational needs and project availability. As an independent contractor, you should anticipate fluctuations in workflow and, therefore, compensation for services when Cohere does not require as many hours of services in a week. Prospective candidates, please be advised: this role involves working with human-generated and model-generated tasks that may involve exposure to not safe for work (NSFW) text content as part of data annotation tasks, including explicit, offensive, or other inappropriate material.

Location: Philippines We are looking for an experienced NetSuite Developer / Engineer to provide ongoing technical support and development for our Oracle NetSuite ERP system. This person will be responsible for troubleshooting technical issues, maintaining and improving custom scripts and configurations, resolving bugs, supporting third-party integrations, and helping ensure that our NetSuite environment remains stable, reliable, and efficient. The ideal candidate is an experienced NetSuite developer who enjoys debugging, problem-solving, and getting to the root cause of technical issues. This role is highly technical, but a basic understanding of accounting and financial workflows is preferred. This is a remote position. Key Responsibilities NetSuite Development and Script Maintenance • Develop, maintain, and modify SuiteScript customizations using SuiteScript 2.x. • Maintain existing custom records, forms, workflows, and scripts. • Write clean, efficient, scalable, and well-documented code. • Follow NetSuite development best practices. • Ensure customizations remain stable and compatible with future NetSuite updates. Technical Troubleshooting and Issue Resolution • Investigate and resolve technical issues affecting NetSuite functionality. • Diagnose SuiteScript errors, workflow failures, custom form issues, and system performance problems. • Perform root-cause analysis to identify recurring issues and implement long-term solutions. • Troubleshoot issues reported by internal users and provide timely resolutions. • Support technical issues affecting financial workflows, billing, and reporting. Bug Fixes and System Maintenance • Identify, prioritize, and resolve bugs affecting custom NetSuite functionality. • Test and validate bug fixes before deployment. • Monitor custom scripts for errors, failures, and governance issues. • Help maintain the overall stability and reliability of the NetSuite environment. Script Deployment and Change Management • Deploy scripts and customizations across Development, Sandbox, UAT, and Production environments. • Follow established testing and change management procedures. • Maintain version control of custom code. • Monitor deployments to ensure successful implementation with minimal disruption to business operations. Integration Support • Troubleshoot issues involving third-party integrations connected to NetSuite. • Assist with maintaining API connections and resolving synchronization errors. • Support testing following integration updates or vendor changes. • Work with external NetSuite partners when additional technical support is needed. Documentation • Maintain technical documentation for scripts, customizations, integrations, and deployments. • Document code changes, bug fixes, troubleshooting procedures, and system configurations. • Create documentation that supports future maintenance, troubleshooting, and knowledge sharing. Collaboration and Technical Support • Work closely with Finance and other internal stakeholders to understand technical requirements and resolve system issues. • Clearly explain technical issues and solutions to non-technical stakeholders. • Collaborate with external NetSuite partners on complex technical issues and system improvements. • Provide technical guidance regarding NetSuite functionality, limitations, and potential solutions. Required Skills and Qualifications • Strong experience developing and maintaining Oracle NetSuite using SuiteScript 2.x. • Proficiency in JavaScript. • Strong understanding of NetSuite development best practices. • Excellent analytical, debugging, and troubleshooting skills. • Ability to quickly diagnose complex technical issues and identify root causes. • Strong attention to detail. • Ability to write clean, maintainable, and well-documented code. • Strong written and verbal communication skills. • Ability to explain technical concepts clearly to non-technical stakeholders. • Strong organizational skills and the ability to manage multiple support requests, development tasks, and deployments at the same time. • Ability to work collaboratively with Finance teams, internal stakeholders, management, and external technical partners. Preferred Qualifications • Basic understanding of accounting and financial workflows, including Accounts Receivable, Accounts Payable, General Ledger, billing, and financial transactions. • Experience troubleshooting third-party integrations and API connections. • Experience working with NetSuite across Sandbox, UAT, and Production environments. • Experience with version control and structured software development processes. Typical Tasks The role may include: • Reviewing and responding to internal NetSuite technical support requests. • Investigating and resolving reported bugs and system issues. • Maintaining and updating existing SuiteScripts. • Monitoring production scripts and resolving execution errors. • Testing script changes and bug fixes in Sandbox or other non-production environments. • Deploying approved scripts and customizations to Production. • Troubleshooting third-party integrations and synchronization issues. • Maintaining technical documentation. The workload will vary depending on active support requests, development needs, deployments, and system issues. How Success Will Be Measured Success in this role will be measured by: • Timely resolution of technical issues and support requests. • Accurate diagnosis and resolution of bugs with minimal recurrence. • Successful script and customization deployments with minimal production issues. • Stability and reliability of the NetSuite environment. • Quality, accuracy, and completeness of technical documentation. • Responsiveness to Finance and internal stakeholder technical requests. • High-quality, readable, and maintainable code that follows NetSuite best practices.

Location: San Francisco, CA SF IDEO Senior BxD Designer IDEO San Francisco is in search of a Senior Business Designer who will frame complex business problems, translate insights into viable growth opportunities, and drive ideas toward real-world activation. The role: At IDEO, we help clients move forward when the path isn’t clear — whether driven by ambition, responding to disruption, or breaking out of entrenched ways of working. As a Senior Business Designer, you’ll help teams and organizations turn bold ideas into viable, real-world outcomes — shaping new products, services, and ventures while building the business models, strategies, and pathways to bring them to market. Working across the spectrum from insight to execution, you’ll use business tools, systems thinking, entrepreneurial creativity, and strategic analysis to drive competitive advantage and strategic growth for our clients. The right person for this role has strong business acumen and strategic instincts, with experience in growth strategy, product management, go-to-market execution, or venture creation. They’re comfortable navigating ambiguity, working with multi-disciplinary teams, influencing senior stakeholders and building conviction for new ideas. They quickly understand how a business creates and captures value, connecting market insights, customer needs, and financial drivers into compelling strategies — moving work forward with the right balance of rigor and creativity to drive real impact. Why is this role important for IDEO’s work? Business Designers make the biggest impact by turning ambiguity into clarity and connecting insights to commercially viable opportunities. Their skillset is critical to our work because they bring together strategy, business decision making, market understanding and business model thinking to help clients create and capture value. We count on them to move work beyond ideas into action and provide clear, informed pathways for winning investments. Once here you will: Creatively problem-solve by generating new ideas, viable business models, value propositions and go-to-market strategies for new products, services, and ventures, exploring unconventional or hidden solutions in a business context Build an understanding of IDEO’s client organizations, and partner with clients to drive change and innovation within their teams and organizations Conduct market, competitive, and financial analysis to identify new and emerging opportunities, inform decisions, shape business cases, and build conviction for new ideas Synthesize research, data, and insights into clear narratives that guide decision-making and align stakeholders Translate complexity into action by developing and leading experiments or pilots that produce insights to help create innovation roadmaps to scale recommendations in real-world contexts Collaborate in multidisciplinary teams with designers across all creative and technical disciplines (design research, interaction design, data science, communication design, etc.) Facilitate client workshops and conversations that drive alignment, momentum, and strategic decisions Continuously grow with, as well as upskill, the Business Design craft through knowledge sharing and bringing unique perspectives to the greater IDEO community Relevant experiences/skills: Qualified candidates for this role will have: A minimum of 4 years of full-time working experience – in a past life, you may have worked in strategy consulting, venture design, product strategy, product management, product innovation, corporate strategy, business insights, business analytics, business planning, go-to market, and/or growth strategy Strong business acumen; i.e., broad knowledge or exposure to strategy, marketing, finance, operations, product development, organizational design, etc — MBA beneficial but not required Experience in business design, strategy, product management, venture building, or innovation roles Ability to creatively problem-solve in a business context, i.e. generate multiple alternative ways to address feasibility, viability, and desirability, including ways that are not obvious Comfort working in ambiguous situations with limited direction, independently shaping problem definitions and approaches Ability to interpret and communicate complex business ideas to different audiences, through text, visual, and verbal communications Experience working across stakeholders and influencing decisions in complex organization Track record in making ideas real and tangible, from concept to execution roadmap, as an entrepreneur and/or intrapreneur, and bringing others along with you Strength in synthesizing qualitative and quantitative data into clear insights, recommendations and narratives, supporting decision making across options and making potential impact clear Strong storytelling and strategic narrative-building skills Standout candidates for this role will bring: Direct experience applying human-centered design approaches, or signals of this skillset Leadership in bringing a new product or venture to market (0→1) Familiarity with tools (including AI) to accelerate thinking and workflow Client centricity (direct experience or signals of this skillset) Experience with venture building, incubation, innovation labs or product/service development Experience in relevant industries (financial services, healthcare, technology, manufacturing), with an understanding of complex environments such as regulation, risk, and product innovation Key mindsets: IDEO Designers are people who: Lead with curiosity and optimism Hold space for authenticity and psychological safety Embrace ambiguity (and still ship) Collaborate generously across disciplines Learn from failure and iterate forward Take ownership and make others successful What does IDEO offer you? IDEO is a place where you can solve diverse, complex challenges for our clients and their organizations, alongside thoughtful, intelligent individuals who lead with curiosity, empathy, and humility. We intentionally craft moments that allow our community to pause, create, and connect. We encourage our community to bring their whole selves to work, respect the need for work-life balance, and allow for autonomy in the design process and your career. As a Senior Business Designer in San Francisco, we provide the opportunity for you to: Work on breakthrough products, ventures (0→1) and strategies across industries like health, financial services, and technology Collaborate with a studio of creative, curious, and deeply thoughtful people who challenge and inspire one another Contribute to a portfolio deeply rooted in real-world, applied innovation with Midwestern makers, healthcare leaders, financial institutions, and digital product organizations Shape end-to-end innovation—from early insight to market activation Grow your craft within deeply multidisciplinary teams while building confidence and leadership in client-facing work Payscale & Benefits IDEO is committed to paying its employees equitably, regardless of gender identity or race/ethnicity/cultural identity. We support the holistic well-being of our community by providing a thoughtfully designed benefits package. The salary range for this role is $100,000-120,000 USD. This range is influenced by a wide range of factors considered in compensation decisions at IDEO. This includes, but is not limited to: skills, industry knowledge, and experience. Final offers may vary from the amount listed based on geography, candidate experience & expertise, and other factors. In addition to base compensation, IDEO offers a rich benefits package including the following: Health Benefits: Vision, Dental, Healthcare Financial Benefits: 401K matching Family & Caregiving: Parental Leave, Adoption Assistance, Fertility Assistance, Transgender Medical Assistance, Breastmilk shipment, Back-up/Dependent Care, Pet Insurance Other Benefits: Flexible Work, Flexible Time Off, Paid Holidays, Annual Education Stipend, Home Office Stipend Commitment to Diversity At IDEO, we are committed to the work of advancing diversity, equity and inclusion within our organization and in the world. Our purpose of having disproportionate, world-changing impact through design is directly connected to our ability to bring many different perspectives to the table. This applies to our candidates, the people we hire, the clients and customers we serve, and the communities we learn from in our research.

Location: Remote US At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About the Product team The Product team listens to our customers’ needs and translates those insights into a clear product vision. The team works closely with design, engineering, and analytics to build scalable financial products that empower people to manage their money with confidence. We rely on empathy, curiosity, and business sense to prioritize features and improve experiences. Our role is to lead with clarity, support cross-functional execution, and champion the user in every decision. About the role The Chief of Staff to the SVP of Product is the strategic thought partner and proxy to the leader. The role exists to scale the product leadership function: by anchoring on the leveraged people problems most central to the org, by owning the external product narrative end-to-end, and by being on point for strategic bets that need a single accountable owner (ex: AI enablement, special projects). The end goal is a healthy Product org with pillar leads running independently at high quality, decisions made with less latency, and a clearer story about where Product is going, and why. What you’ll do Design and run the product leadership team’s rhythms (staff meetings, product reviews, all-teams, offsites): agenda architecture, pre-reads, decision capture, follow-through Co-own the people rhythms with the HRBP across hiring, calibrations, performance, and talent reviews. Surface emergent structural risks (broken hiring funnels, attrition signals, single points of failure) with proactive solutions Partners with Technology Operations function to define and improve processes for roadmap planning, driving prioritization decisions, setting annual OKRs and tracking progress to goals throughout the year Own headcount planning and budget management alongside the Finance and HR Business Partners: annual planning, quarterly reforecasts, hire-prioritization tradeoffs Drive AI retooling and enablement, including running internal AI masterclasses for leadership and natively embedding AI-enabled processes across the function Curate the external product narrative (all-hands, written updates, major external talks): operate as a speechwriter, partnering with PR, comms, and brand Prepare executive briefings and leadership communications, and reduce decision latency across the Product leadership team Run a recurring org health pulse (engagement scores, regrettable attrition, leveling drift, manager effectiveness), escalating early signals before they become structural problems What you’ll bring 10+ years in roles that built product credibility and strategic-narrative chops: strategy with deep product partnership, or a prior CoS role to a senior product or engineering executive at a high-growth tech company A track record of running people processes at scale (hiring, calibrations, leveling, talent reviews) in a fast-growing organization Exceptional written communication: you can ghostwrite, synthesize narrative from raw inputs, and draft a board page that holds up under scrutiny Pattern-matching for organizational dysfunction: the muscle to spot a broken hiring funnel, a single point of failure, or a leadership gap before anyone names it Comfort operating with influence and without authority across senior leaders in Product, Engineering, Design, Revenue, Finance, and HR Strong analytical foundation and business acumen: fluent enough in product metrics, financials, and growth analytics to reason about tradeoffs without delegating every quantitative question Why this role matters Affirm’s next phase of growth depends on Product moving from a function powered by heroics to a function powered by a world-class operating system. The Chief of Staff is the linchpin of the strategic side of that change: the partner who helps make the strategy clear, the org stronger, and the leader’s leverage real. Base Pay Grade - S Equity Grade - USA11 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.) USA base pay range (CA, WA, NY, NJ, CT) per year: $255,000 - $335,000 USA base pay range (all other U.S. states) per year: $226,000 - $306,000 Please note that visa sponsorship is not available for this position. #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: Palo Alto, California, United States About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role Nebius Token Factory is looking for scientists who can turn frontier LLM and VLM inference bottlenecks into research questions, conduct rigorous experiments, and translate their findings into production capabilities. You will own focused research and optimization projects, write strong code, and produce prototypes, publications, and technical artifacts that engineers can build on. Your research will span quantization, distillation, speculative decoding, KV-cache optimization, and model/runtime co-optimization, alongside inference engines and distributed inference architectures. You will investigate how these approaches interact, evaluate their trade-offs across model quality, latency, throughput, memory footprint, and cost per token, and work with engineering teams to bring promising results into production. Your responsibilities : Lead research projects in efficient LLM and VLM inference, from hypotheses and experiments through ablations, prototypes, and production handoff. Develop and evaluate methods spanning quantization, quantization-aware training (QAT), distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, and collaborate with MLEs and platform engineers to turn them into production components. Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation (PDD). Evaluate how queueing, KV-cache transfer, worker placement, and prefill/decode capacity allocation affect latency, throughput, and serving cost. Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism (WideEP). Study expert placement, load imbalance, and computation/communication trade-offs, and use the findings to guide model and system architecture choices. Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Compare serving architectures under consistent workload conditions and GPU budgets. Work with MLE, GPU kernel, backend infrastructure, product, and customer teams to select research priorities with measurable production impact. Share results through internal reports, technical blogs, papers, and open-source artifacts, and mentor engineers and scientists on experimental design, scientific rigor, and model/system trade-offs. Must-haves : A PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline. A strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas. Strong Python and PyTorch implementation skills, with the ability to turn ideas into experiments and working prototypes. Deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs. Strong experimental design skills covering ablations, baselines, metrics, statistical reasoning, and failure analysis. Excellent written and verbal communication. Nice - to - have s : First-author publications at venues such as NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, or HPCA. Experience deploying ML models or inference optimizations in production. Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals. Experience applying post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation to inference quality or efficiency. Open-source research artifacts, widely used benchmarks, technical blogs, or invited talks demonstrating contributions to efficient AI systems. Research or implementation experience in one or more areas of distributed inference system architecture, such as LLM request routing, PDD, multi-node serving, or MoE expert parallelism, including WideEP. Key employee benefits in the US: Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. 401(k) plan: Up to 4% company match with immediate vesting. Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. Remote work reimbursement: Up to $85/month for mobile and internet. Disability & life insurance : Company-paid short-term, long-term and life insurance coverage. Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $195,200 — $262,200 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Palo Alto, California, United States About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role Nebius Token Factory is building an AI training and model post-training capability for frontier model improvement. This role owns the infrastructure that makes large-scale training and RL experiments possible, reliable, reproducible, and efficient. The work sits at the intersection of distributed systems, GPU performance, model training frameworks, RL pipelines, and production engineering. A Senior Machine Learning Engineer owns substantial ML work end to end. They can translate an ambiguous capability goal into concrete experiments, implement and debug training and RL recipes, build the supporting data and systems, and deliver measurable improvements in model quality, experiment throughput, and reliability. They are deeply hands-on and can independently debug both model-behavior failures and distributed training failures. Your responsibilities : Design and run model-training and post-training experiments, including SFT , continued pretraining, preference optimization ( DPO /IPO/ KTO ), and RL methods such as RLHF / RLAIF , PPO , and GRPO . Build reward functions, judge models, verifiers, task environments, and evaluation sets for reasoning, coding, tool use, and agentic workflows. Create synthetic data and data pipelines, including teacher-student generation, self-play, rejection sampling, filtering, and quality scoring. Analyze model-behavior failures and turn them into targeted data, reward, or algorithm improvements. Build and maintain distributed training and RL infrastructure using frameworks such as Megatron- LM , DeepSpeed, PyTorch FSDP /DTensor, Ray, verl, slime, AReaL, or OpenRLHF. Implement and debug parallelism strategies (tensor, pipeline, sequence/context, expert, and data parallelism) and build reliable rollout, reward-serving, checkpointing, and experiment-orchestration components. Profile and improve GPU utilization, memory usage, communication efficiency, training throughput, and inference/serving performance. Design rigorous evaluations and ablations for capability, instruction following, reasoning, tool use, safety, and regression risk. Write clear experiment plans, design docs, benchmark reports, and runbooks, and partner across research and platform teams. Must-haves : Strong Python and PyTorch engineering skills, with the ability to move quickly from idea to experiment to working system. Hands-on experience across at least two of: model training, post-training/ RL , applied modeling, data pipelines, or large-scale ML systems. Ability to design rigorous experiments with baselines, ablations, metrics, and failure analysis. Practical understanding of modern LLM behavior, instruction tuning, preference optimization, and evaluation challenges. Practical understanding of transformer training bottlenecks, memory pressure, communication overhead, and checkpointing. Ability to reason quantitatively about model quality, throughput, utilization, reliability, cost, and research velocity. Strong communication skills and ability to collaborate with researchers, engineers, and leadership. Nice - to - have s : Experience with LLM post-training, RL , agents, reward modeling, synthetic data, or model evaluation. Experience with RL frameworks or pipelines such as verl, slime, AReaL, OpenRLHF, TRL , or custom PPO / GRPO / RLHF systems. Experience with Megatron- LM , DeepSpeed, PyTorch FSDP /DTensor, Ray, Slurm, or Kubernetes on large GPU clusters. Familiarity with NCCL , CUDA , Triton, Nsight, InfiniBand/ RDMA , and H100/H200/B200 clusters, or with model serving and inference optimization. Publications, open-source contributions, or production impact in LLM post-training, RL , reasoning, coding models, synthetic data, distributed training, or evaluation. Experience designing agent environments, tool-use tasks, or verifier-based rewards. Key employee benefits in the US: Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families. 401(k) plan: Up to 4% company match with immediate vesting. Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. Remote work reimbursement: Up to $85/month for mobile and internet. Disability & life insurance : Company-paid short-term, long-term and life insurance coverage. Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $195,200 — $262,200 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: San Francisco, CA | 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's Enterprise AI Products team builds what makes Claude a daily-use tool for enterprise customers across industries. We focus on organizational context and workflows (plugins, skills, connectors, webhook-triggered processes / agents). In other words, we focus on products that form the connective tissue that lets Claude operate across an organization. A big part of this work is understanding what's blocking adoption and building the capabilities that close those gaps. Much of this is being built 0→1 right now: you'll be shaping the product and the architecture in a market where no one has done this well yet. You'll be a technical leader who thinks holistically about the end-to-end customer experience, partners directly with research to push model capabilities into production, and carries real ownership over what we ship next. What you'll do Own technical design and delivery for enterprise-facing core products, end-to-end across the stack Partner with product, design, and go-to-market to turn enterprise customer workflows into shipped product, not just execute against a spec Set technical direction and standards for your team: architecture, code quality, and how the team builds Work directly with enterprise customers and sales during key conversations, translating what you learn into engineering priorities Work closely with research to make the models better in your domain: shaping evals, surfacing failure modes, and feeding customer learnings back into model development Mentor other engineers and raise the technical bar across the team, working with influence rather than authority Build multi-player, asynchronous agents: department-level processes that are goal-oriented, many-step, and triggered by a webhook, a form, or an email rather than a person typing You may be a good fit if you Have 8+ years of software engineering experience, ideally with 2+ years at a Staff or equivalent technical leadership level Have led the design and delivery of complex enterprise or B2B products across the full stack Have built AI products and know what it takes to turn model capabilities into applications people actually use Are comfortable working directly with enterprise customers and translating what you learn into technical decisions Have built products from 0 to 1 in fast-moving environments, and can set technical direction with limited precedent to lean on Drive cross-team alignment to ship impactful work, with influence over authority Strong candidates may also have Experience working with research to improve domain-specific model capabilities, including evaluation frameworks Experience building extensibility surfaces (plugins, integrations, agent tooling) that third parties or internal teams build on Exposure to both product-led growth and direct enterprise sales 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: Brownsville, WI Corporate Office Improving America’s infrastructure isn’t for the weak. It takes grit, determination, and hard work to execute high impact projects. Michels Corporation engages 8,000 people and 18,000 pieces of heavy equipment in our insatiable drive to be the best. Our work improves lives. Find out how a career as a Heavy Equipment Mechanic can change yours. As a Heavy Equipment Mechanic, your key responsibility will be to perform basic tasks in repairing and maintaining construction or utility related equipment. You will perform preventative maintenance and maintain functional condition of equipment by repairing engine failures, replacing parts, repairing body damage, etc. Why Michels? We are consistently ranked among the top 10% of Engineering News-Record’s Top 400 Contractors Our steady, strategic growth revolves around a commitment to quality We are family owned and operated We invest an average of $5,000 per employee on training each year We reward hard work and dedication with limitless opportunities We believe it is everyone’s responsibility to promote safety, regardless of job titles We offer a comprehensive benefits program, including Health, Dental, Life, Flexible Spending Accounts, Health Savings Account, Short Term and Long Term Disability Insurance, 401 (k) plan, Legal Plan, and Identity Theft and Monitoring Plan. Depending on your position and location you may participate in a different benefit plan. Why you? You thrive in fast-paced environments under tight deadlines You relish new challenges and evolving technology You enjoy collaborating and communicating with your teammates You like to know your efforts are noticed and appreciated You have a strong attention to detail You enjoy working independently What it takes: 2-5 years of experience working on construction or utility related equipment Hydraulics, drive train, controls and electrical diagnostics experience (desired) Welding experience (desired) Basic computer proficiency Ability to move/operate heavy equipment (desired) Ability to provide own basic hand tools AA/EOE/M/W/Vet/Disability https://www.michels.us/website-user-privacy-policy/

Location: London, England, United Kingdom About Us Fanatics is a leading global sports platform redefining how fans connect with the teams, players and moments they love. Our businesses — Fanatics Commerce, Fanatics Collectibles, Fanatics Betting & Gaming, Fanatics Events, Fanatics Advertising, Fanatics Markets and Fanatics Studios — maximize the presence and reach for hundreds of partners globally and create a one-stop experience that allows fans to buy, bet, collect, and earn, while engaging with sports in deeper, more immersive ways. This includes licensed fan gear and lifestyle products, sportsbook and iGaming, physical and digital trading cards, live events, premium sports entertainment content, credit card offerings and more. Together, they form a powerful, integrated ecosystem — connected by the Fanatics ONE loyalty program and FanCash, the currency of sport — delivering personalized experiences to over 100 million fans worldwide. Fanatics holds partnerships with over 900 sports properties, from professional leagues and players’ associations to teams, colleges and retail partners; over 7,000 athletes and celebrities; and over 2,000 retail locations, including all Lids stores. Backed by a team of more than 22,000 employees, Fanatics is committed to relentlessly enhancing the fan experience. Data Engineer III About the Role We're looking for a Data Engineer III to join our Data Engineering team, which builds and governs the data foundation that powers the business. You'll work within our stack — Python ingestion pipelines, Airflow orchestration, and Snowflake/Databricks — helping move data reliably and securely from source to decision-ready output. You'll implement features and fixes against a given design, handle known classes of pipeline issues on your own, and escalate genuinely novel problems with clear context rather than working them in isolation. You're also expected to start contributing meaningfully in code review — catching real bugs, not just style nits. What You'll Do Implement new ingestion sources end-to-end against a senior engineer's design — connector code, DAG, schema, monitoring, and catalog registration — extending the team's existing framework where a new source needs a pattern it doesn't yet support Investigate pipeline failures independently, recognize known classes of issues, and ship the documented fix without needing to escalate Before shipping a new pipeline, identify downstream consumers and what would break if data were late or wrong, and flag gaps like this during spec review — before writing code Write clear handovers when escalating a genuinely unresolved issue — what you tried, what you ruled out, and where things diverge — so a senior can pick up without re-discovery Review peers' pipeline PRs and catch non-obvious issues (e.g., missing idempotency checks, race conditions) that could cause incorrect downstream data Turn ambiguous "why is this data wrong?" questions into structured investigations — tracing data lineage from source to warehouse and communicating back what you found Surface concerns in spec review as specific, well-reasoned questions rather than staying silent or blocking progress Support data security and governance work (e.g., PII masking, access controls) and contribute to data delivery work, including reverse ETL integrations Build strong working relationships with internal stakeholders and help scope and clarify requirements for new work Mentor DE2s on their first significant projects — pairing on tricky decisions and helping them apply team conventions What We're Looking For 3–5 years of professional software or data engineering experience Strong SQL and Python skills, with solid experience building and operating production data pipelines Comfort investigating and root-causing pipeline issues independently before escalating Experience with workflow orchestration tools (Airflow or similar) and a cloud data warehouse/lakehouse (Snowflake, Databricks, or similar) Solid understanding of data pipeline concepts: idempotency, schema evolution, backfills, and data quality/testing Experience giving substantive code review feedback, not just style or formatting comments Strong communication skills — can write a clear technical handover, ask sharp questions in spec review, and explain a data lineage investigation to a non-technical stakeholder A track record of taking ownership of known-class problems end-to-end rather than needing step-by-step direction Nice to Have Experience extending or building reusable pipeline frameworks/templates Exposure to reverse ETL tools or patterns, PII masking, or data access governance (RBAC) Exposure to observability/monitoring tooling (e.g., Datadog) for pipeline health and alerting Some experience mentoring or informally supporting more junior engineers Background in gaming, betting, e-commerce, or another regulated/high-compliance industry Why Join Us Real ownership over known-class problems, with senior/staff support available for the genuinely novel ones Work on high-visibility, high-trust systems that the business depends on A culture built around clear tenets: standardize before you scale, own the outcome (not just the ticket), and clarity over complexity Clear growth path into Senior Data Engineer, with room to start mentoring and shaping team practices along the way By submitting your application, you agree to our terms of service and acknowledge you have read our Candidate Privacy Policy. Fanatics will never ask candidates for money, banking information, or other sensitive personal information as part of the interview process. If you receive a suspicious message claiming to be from Fanatics recruiting, please do not respond and report it here .

Location: Global Anywhere Who We Are: Alpaca is a US-headquartered, global leader in agent-first brokerage infrastructure for stocks, ETFs, options, crypto, fixed income, 24/5 trading, and more. Amongst our subsidiaries, Alpaca is a licensed financial services company, serving hundreds of financial institutions across 40 countries with our institutional-grade APIs. This includes broker-dealers, investment advisors, wealth managers, hedge funds, and crypto exchanges, totalling over 10 million brokerage accounts. Our global team is a diverse group of experienced engineers, traders, and brokerage professionals who are working to achieve our mission of opening financial services to everyone on the planet. We're deeply committed to open-source contributions and fostering a vibrant community, continuously enhancing our award-winning, developer-friendly API and the robust infrastructure behind it. Alpaca is proudly backed by $400 million in funding from top-tier global investors including Portage Ventures, Spark Capital, Tribe Capital, Social Leverage, Horizons Ventures, Opera Tech Ventures, SBI Group, Derayah Financial, Unbound, Peak XV, Elefund, and Y Combinator. Our Team Members: We're a dynamic team of 400+ globally distributed members who thrive working from our favorite places around the world, with teammates spanning the USA, Canada, Japan, Hungary, Nigeria, Brazil, the UK, and beyond! We're searching for passionate individuals eager to contribute to Alpaca's rapid growth. If you align with our core values—Stay Curious, Have Empathy, and Be Accountable—and are ready to make a significant impact, we encourage you to apply. Your Role As a Senior Software Engineer on the Platform team, you will build and own the frameworks, tooling, and CI/CD infrastructure that let Alpaca’s engineers ship new features quickly and reliably. This is a software engineering role at its core: you will spend most of your time writing Go, designing automated test frameworks, and digging into application code and Kubernetes when needed. Just as importantly, you will help redefine how we use AI to raise the bar on quality - leveraging LLMs and AI-driven tooling to generate tests, catch regressions before they ship, and turn every incident into durable, automated coverage. We are looking for engineers who treat quality as an engineering discipline and see AI as a force multiplier for it - people who build the systems that make testing fast, reliable, and effortless for the teams that depend on them. Things You Get To Do Design and build automated test frameworks across our REST and gRPC API surface. Leverage AI and LLM-based tooling to accelerate test generation, harden regression coverage, and turn production incidents into automated tests - embedding these practices into the frameworks the whole engineering org relies on. Build and maintain CI/CD pipelines - we use a mix of GitHub Actions and Google Cloud Build. Design and execute load, stress, and scalability tests to ensure our platform can handle growing demand. Introduce chaos engineering practices - designing fault-injection and resilience experiments that surface failure modes before our customers do. Standardize tooling and infrastructure to improve the day-to-day developer experience. Partner with other teams to raise test coverage, reliability, and speed across services. Dig into application code to root-cause failures and drive fixes to completion. Mentor and guide product engineers, fostering a culture of quality and continuous improvement. Who You Are (Must-Haves) You have 5+ years of experience as a software engineer building and maintaining production systems. You have written code in strongly typed languages and have at least 1 year of experience with Go. You are fluent with AI-assisted engineering - you actively use LLM-based tools in your workflow and have a clear point of view on where they elevate quality (and where they don’t). You have built and maintained CI pipelines before - ideally with GitHub Actions or Google Cloud Build. You have designed and built automated test frameworks, and you understand the challenges microservices pose for reliable integration and end-to-end testing. You are familiar with Kubernetes beyond the basics - you can write a Helm chart for a new service with relative ease, you understand best practices around security, and you have prior job experience or certifications to prove this. You have worked at a startup before - you understand that things don’t always go according to plan, that there is significant technical debt, that some tasks just need to be done, and that sometimes there are no processes or documentation to guide your hand. You are not afraid of taking a task from start to finish - gathering requirements, figuring out and implementing the best technical solution, then deploying and monitoring the results. Who You Might Be (Bonus Points) You have used AI/LLM tooling to build QA automation - test generation, flaky-test triage, or incident-to-regression pipelines - and can speak to what worked and what didn’t. You have written code in Python or TypeScript, and can build efficient Dockerfiles and secure container images. You have implemented load tests with k6 (REST) and ghz (gRPC) and have experience analyzing pprof/trace output. You have done IaC deployments with Argo CD or Terraform, or have used Google Cloud Platform and Google Kubernetes Engine before. You are familiar with Tilt and have written a Kubernetes Operator before. You have practiced chaos engineering - running fault-injection or resilience experiments with tools like Chaos Mesh, LitmusChaos, or Gremlin. You are familiar with testing event-driven systems using Kafka (or even better, Redpanda). How We Take Care of You: Competitive Salary & Stock Options Health Benefits New Hire Home-Office Setup: One-time USD $500 Monthly Stipend: USD $150 per month via a Brex Card Alpaca is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce. Recruitment Privacy Policy

Location: United States, San Mateo, CA Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Summary Would you like to help ensure the quality of PlayStation® peripherals and firmware? Join the team delivering innovative test solutions for PlayStation® Link™ devices, where your work will directly impact performance, stability, and the player experience. Sony Interactive Entertainment has a great opportunity in the Quality Engineering department! We are seeking a self-motivated engineer with strong Python and test automation skills and a focus on quality, consistency, and thoughtful testing practices. As a Software Development Engineer in Test Contractor, you’ll work hands-on with our peripherals and own automated test coverage for specific features across multiple platforms, alongside senior engineers. We value teamwork and continuous learning. Responsibilities In this role, you'll work where firmware, hardware, and platform software meet, building the tests that check them and keeping that automation healthy. Write Python automation suites for firmware and platform features Perform integration testing on PlayStation® 5, PlayStation® Portal, and Windows Improve the shared automation frameworks and test infrastructure Troubleshoot test failures, using execution data to find flaky or slow tests Collaborate with QA, Development, and Product teams to align on test coverage Qualifications We’re looking for someone who’s as comfortable writing test code as working out why it failed. Strong Python skills, including writing automated tests in pytest and Appium with minimal supervision Experience with Git for version control Experience configuring Jenkins CI/CD jobs and troubleshooting pipeline failures Experience using test case management tools like qMetry or TestRail Effective communication and collaboration skills in a cross-functional team Bachelor's degree in CS, Engineering, or related field, or equivalent experience Nice to Have If you bring any of these, we’d love to hear about them! Understanding of embedded firmware testing, including basic electrical concepts like current draw, voltage levels, and battery diagnostics Experience testing or interacting with Windows-based drivers Familiarity with PlayStation® SDK development Experience programming in C or C++ (modern C++ preferred, e.g., C++17) At SIE, working with our partners, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the individual base pay range may vary based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for benefit offerings that include medical, dental, and vision. Click here to learn more. The estimated base pay range for this role is listed below, this is an hourly rate. $52 — $78 USD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.