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Location: Buenos Aires, Argentina; Medellín, Colombia; Bangalore, India; Guadalajara, Mexico; Lahore, Pakistan Workplace: fully We’re a remote, product-focused startup building AI- and algorithm-driven systems, and we’re looking for a strong Backend Django Engineer who loves clean data models, well-designed APIs, and clever algorithms. You’ll own core backend features end-to-end: from modeling the data to implementing the logic and exposing it through fast, reliable services that ship to users quickly, working with a small distributed team across several countries. 💰 $100 Bonus Opportunity: Candidates who successfully complete the coding assessment and meet our quality standards may be invited to an additional evaluation stage. Candidates who successfully pass this stage and are selected to proceed to the final interview will receive a $100 bonus . To be considered for the assessment, please submit your resume through this job application. If your resume is approved, we’ll send you the coding assessment with further instructions. What You’ll Do Design and implement backend services and APIs using Python + Django (and DRF or similar). Model and evolve our domain in the database with clean, well-structured schema s and relationships. Implement algorithmic/AI logic in the backend (e.g., scoring, ranking, routing, decision rules). Write pragmatic, production-ready code that’s easy to reason about and iterate on. Optimize for correctness and performance : efficient queries, smart indexing, and lean responses. Work with the team to turn product ideas into concrete technical designs and endpoints. Help shape how we build things: patterns, conventions, and how we ship and iterate as we grow. What We’re Looking For Strong experience building backend applications with Python + Django . Solid understanding of relational data modeling and SQL (we use PostgreSQL). Comfortable designing and building RESTful APIs (bonus if you’ve used DRF or similar frameworks). Experience working on non-trivial business logic or algorithms (e.g., decision flows, scoring rules, optimization logic). Good instincts around performance : understanding query behavior, avoiding obvious pitfalls, and using caching when it counts. A startup mindset : comfortable with ambiguity, moving fast, and iterating based on real- world feedback. Ability to work independently in a remote environment and communicate clearly. Bonus Points For Experience in startups, side projects, or hackathons where you’ve had to ship scrappy solutions fast. Background in algorithms, optimization, or data-heavy systems. Experience with Google Cloud Platform (GCP) in production. Familiarity with Redis (caching, queues) and PostgreSQL at some scale. Exposure to containers and orchestration (Docker, Kubernetes) and/or serverless on GCP. This role is a central piece of our backend roadmap , and we’re aiming to fill it quickly once we meet the right person. If it resonates with you, go ahead and apply now. Send us your resume to start the assessment process (and get a chance at the $100 bonus).

Location: North America - Remote Workplace: Remote Douro Labs is the core development team behind the Pyth Network. We're looking for a Market Analyst to track the crypto markets, specifically prediction markets and perpetual futures, and turn that understanding into business opportunities for Pyth. This role is for an analyst who can read the market and explain why it matters to us: someone who can pull on-chain and venue data to quantify a new trend one hour and write the report that convinces the team to act on it the next. You will serve as our eyes on two of the fastest-moving areas in crypto, covering the market side (monitoring events, trader conversations, volumes, and new venues across prediction markets and perps) and the product side (translating that research into a clear picture of our users and concrete opportunities for Pyth). - Location: Remote (US or Europe) - Type: Full-time - Reports to: Head of Technical Operations About Our Team and Your Role We are a well-rounded team: half of us are tech whizzes, while the other half excel in building partnerships with institutional clients, prime brokers, and the global financial infrastructure community. Curiosity and rigor are key to how we operate. Remote Work: Our team is spread across the globe, from the US and South America to Europe and Asia. We are a digital-first organization where remote work is the norm. Startup-level Speed: We thrive in the dynamic DeFi space and need an analyst who can go from question to answer quickly, without waiting for direction. The Mission: You will be shaping how Pyth grows in prediction markets and perpetual futures. As these markets expand and new venues launch, your research will inform where we build next and how we serve the teams building on our data. About the Role This is a hybrid research/strategy role. At the outset, you'll monitor prediction markets and perps day to day and connect what's happening to our business. Over time, your research is expected to directly shape product decisions and new opportunities across Pyth. We want research that leads to action: every piece of work should end with a clear view on what it means for Pyth and what we should do about it. Responsibilities Market Monitoring - Track news, launches, and structural shifts across prediction markets and perpetual futures - Monitor the conversations where traders are active, including X, Discord servers, Telegram groups, and other trader communities, to spot sentiment shifts and emerging trends early - Follow volumes, open interest, funding rates, and market share across major venues - Connect recent events to their impact on Pyth and share timely takeaways with the team - Maintain a current view of the competitive landscape, including oracles and data providers serving these markets User Research - Research prediction market and perps protocols to understand how they use price data - Map who our users are, what they need, and where current solutions fall short - Build dashboards and datasets the team can use to follow these markets Product Opportunities - Turn research findings into concrete product ideas for Pyth - Size opportunities using market and on-chain data - Work with product, engineering, and BD to prioritize and pressure-test ideas - Track how launched initiatives perform against the original thesis Research and Reporting - Write clear, convincing research reports for internal and external audiences - Present findings and recommendations to leadership - Build a repeatable research process the team can rely on About You - Background as an analyst at a crypto research firm or in a research/data role at a perps exchange or prediction market - Deep understanding of prediction market and perpetual futures market structure - Active in trader communities and comfortable picking up signal from X, Discord, and Telegram - Proficient with data analysis tools (SQL, Python, Dune or similar) - Strong writer with a track record of research that drives decisions - Analytical and a self-starter, comfortable owning a research agenda independently - Comfortable with startup pace and evolving scope Think you've got what it takes to build the most talented team in the world? We'd love to meet you.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Hardware is becoming critical to how AI gets built, and the legal questions are as new as the technology. We're hiring a Commercial Counsel, Hardware to help Anthropic's product teams move fast, build safely, and get the legal calls right. In this role, you'll negotiate a high volume of fast-moving deals for hardware, components, software, and emerging technology procurement needs. This role will also lead multifaceted technology, data, and partnership deals, many of them the first of their kind at Anthropic. You'll be the legal and risk partner that technical and business leaders turn to when they need a fast, practical read on a deal or purchase. You'll clear low risk transactions quickly, spot the ones that deserve a closer look, and build scalable solutions as new complexities come up, all while working alongside Procurement and Finance and Legal colleagues in areas like privacy, IP, and trade. Along the way, you'll also support partnerships with major tech companies, universities, and media organizations, which gives you a view across much of the business. Key responsibilities Negotiate and close a high volume of agreements for hardware and components, including review of embedded firmware and companion software licenses Structure and negotiate complex technology, data, and partnership agreements Track legal and regulatory changes that affect hardware products and components, such as product safety rules and restrictions on foreign-made components, and explain what they mean for our plans Identify trade, export control, sanctions, and supply chain concerns in cross-border sourcing, and work with our national security and compliance teams to resolve them Build and maintain self-serve guidance, templates, and AI-assisted review tools so routine purchases don't wait on Legal Manage outside counsel for specialist questions and overflow volume Cover other technology or hardware transactions on the Legal team as needed Minimum qualifications Hold a law degree (JD, LLB, or equivalent) and meet the local licensing requirements to work as in-house counsel where you'll be based Hands-on experience buying hardware and firmware, components, and software in high volume, fast-paced environments Deep experience leading complex deals, such as technology or data licensing, joint development, or supply partnerships Working knowledge of international supply chains and how sourcing choices (and their associated risks) show up in contracts (lead times, single-source risk, warranties, country of origin, higher risk jurisdictions) Working knowledge of trade and regulatory compliance for hardware, including export controls, sanctions, tariffs and customs Clear, plain communication with scientists, engineers, and operators, so legal risk turns into a decision they can act on A low-ego, "doer" attitude and real interest in taking on work outside your core practice area Intense curiosity about AI and emerging hardware, and a commitment to responsible AI development Preferred qualifications At least 8 years of legal experience in hardware or a closely related technical space, with the judgment to run risk assessments and deals on your own from day one In-house time at a hardware-intensive technology company (such as electronics, industrial automation, or complex devices) while it was scaling quickly Experience supporting product or engineering teams as a dedicated counsel Experience with facilities or on-site vendor services, including the insurance and safety questions An engineering, product, or other technical background Experience using AI tools to speed up your own legal work Role-specific policy: For this role, we expect all staff to be able to work from our San Francisco office at least 3 days a week, though we encourage you to apply even if you might need some flexibility for an interim period of time. 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: $335,000 — $385,000 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 As a Marketing Analytics Lead at Anthropic, you will own how we measure marketing. You'll build and run a single measurement framework that shows how marketing activity turns into pipeline, revenue, and product usage, and you'll make that framework something marketers and executives actually use to make decisions. As our marketing programs grow across enterprise and product-led motions, your work will determine whether we invest in what works. In this role, you'll own the marketing measurement framework end to end: the metric definitions, the data models behind them, the dashboards that surface them, and the insights they produce. This is a hands-on individual contributor role; data science and data engineering will support you, but you'll do the core work yourself. You'll partner closely with field marketing, partner marketing, campaign marketing, finance, sales strategy, sales development, data science, and data engineering to align on definitions and keep the whole organization working from one view of the funnel. Key responsibilities Own the marketing measurement framework that connects marketing activity to pipeline, revenue, and product usage Set the direction for the framework and extend it to programs it doesn't cover yet Define marketing metrics clearly and get cross-functional teams to agree on definitions early Build and maintain the data models that power marketing reporting Develop dashboards that marketers and executives rely on in their weekly reviews Teach marketers and executives how the metrics work, and keep teaching as the metrics evolve Lead adoption of the framework so that both marketing and executive teams use it as their shared source of truth Partner with finance, sales strategy, and sales development to connect marketing measurement to the broader revenue picture Find and share the insights nobody asked for, turning analysis into recommendations that change what we do Write analytical SQL on large datasets to answer questions about funnel performance and attribution Track framework gaps and data quality issues, and work with data engineering to resolve them Present findings to marketing leadership and executives in clear, decision-ready formats Minimum qualifications Have deep experience with marketing analytics, including lead funnels, attribution to enterprise pipeline, and product usage measurement Have designed metrics from scratch and know what makes a metric trusted and useful Can write analytical SQL on large datasets with confidence Have built data models in tools like dbt and dashboards that many people use daily Are comfortable setting direction without waiting for a plan to be handed to you Can turn vague questions into clear, measurable definitions Work well across functions and know how to get teams aligned on definitions before problems surface Enjoy teaching others how metrics work and helping non-technical audiences build data fluency Finish what you start, from first definition to adopted dashboard Are excited about Anthropic's mission to develop AI that is safe and beneficial Preferred qualifications Experience building marketing measurement for both enterprise sales-led and product-led growth motions Familiarity with marketing attribution models and their practical tradeoffs Experience presenting metrics and insights directly to executives and shaping how leadership reviews performance A background in data science, analytics engineering, or marketing operations Experience working with CRM and marketing automation data, such as Salesforce and related tooling Experience standing up a measurement practice where one didn't exist before Familiarity with how finance and sales strategy teams think about pipeline and forecasting 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: $255,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote, Canada; Remote, United Kingdom; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. About the Role We are looking for a Distinguished Engineer to lead technical direction across GitLab's Core DevOps services, the systems the majority of our users touch every day. Distinguished Engineers are recognized experts across multiple technology domains and represent the most senior level of technical leadership within and across divisions at the company. Core DevOps builds continuous Integration, continuous deployment, planning, and source control experiences. These are among the most mature, highest traffic, and most deeply interconnected systems at GitLab. They carry years of accumulated architectural decisions, they sit in the critical path of our customers' own delivery pipelines, and they are being reshaped by the shift toward AI native development. The job is to raise their quality, converge them onto a coherent go-forward architecture, and retire accumulated risk, all without interrupting the millions of users and Fortune 100 organizations who depend on them. GitLab is pursuing a set of company-wide engineering goals: large gains in developer productivity, measurably higher quality in what we ship, and engineering practices reshaped around AI and agentic workflows. Core DevOps is where much of that strategy has to land, because these are the services our own engineers and our customers depend on daily. In this role you will bring that strategy into Core DevOps in a form that works for long lived production systems, and carry what you learn here back out to the rest of engineering. What You'll Do Set and continuously refine the go forward technical direction for CI, CD, Plan, and source code experiences, aligned against the horizontal architectural initiatives. Work directly with the VP of Engineering as her technical counterpart on planning, technical investment, and where the group's engineering effort should go. Translate GitLab's company-wide productivity, quality, and AI native engineering goals into concrete technical direction for Core DevOps, and turn into iterable roadmaps, partnering broadly across the org. Define what good means in measurable terms for these services, including availability, latency at p95 and p99, pipeline success rate, test reliability, data correctness, and defect escape rate, then hold designs and implementations to it. Maintain a clear and current picture of systemic technical risk across the group, including single points of failure, unowned critical paths, brittle coupling between CI/CD and Plan, scaling limits, and past decisions that now constrain the roadmap. Drive a prioritized plan to retire it. Lead the hardest design decisions hands on, writing code, prototypes, and proofs of concept where a design argument needs evidence behind it. Drive convergence on shared patterns, libraries, and paved paths, reducing how many different ways the same problem gets solved across the group. Design migration paths that let large, long lived systems change underneath users without breaking them, using incremental cutover, dual run, measurable rollback, and deprecation with clear timelines. Adopt the platform capabilities coming from GitLab's AI organization and the company's productivity initiatives into Core DevOps, feed this group's requirements back into them, and help prove what works on systems of this scale and maturity. Serve as the escalation point for complex or contested technical decisions across the group, including those where no single team owns the outcome. Review significant designs and merge requests in the group's critical paths, and use review to teach rather than only to gate. Ensure designs hold across GitLab.com, GitLab Dedicated, and Self-Managed deployments, and respect multi-tenant, compliance, and data governance boundaries in each. Partner with Infrastructure, Security, and SRE so Core DevOps services are observable and debuggable, and so failure modes degrade gracefully instead of cascading. Make architectural constraints and opportunities clear to Product in roadmap terms, so that technical investment and product ambition get planned together instead of traded off late. Write clear, opinionated design documents, architecture narratives, and decision records that let teams across the group make aligned decisions independently. Grow Principal and Staff Engineers across Core DevOps, raise the bar on design rigor and technical writing, and contribute to the technical hiring bar for senior individual contributors. Participate in the Incident Management on-call rotation to help meet availability goals for GitLab.com, and complete Interview Training to participate in hiring as a technical interviewer or panel member. Take part in on-call or operational support where your team’s ownership model requires it. What You'll Bring 10+ years of software engineering experience, including 4+ years in a Staff, Principal, or equivalent senior technical leadership role. Deep expertise in AI and ML systems, including large language models, agentic frameworks, and autonomous workflow design at production scale. Proven track record of leading hands-on technical experimentation, including defining evaluation frameworks, running benchmarks, and translating findings into scalable architecture decisions. Strong background in scalable, multi-tenant distributed systems, including service decomposition, fault tolerance, observability, and operational resilience. Experience designing and implementing human-in-the-loop controls, safety guardrails, and responsible AI practices for production systems. Experience mentoring senior engineers and influencing technical direction across multiple teams or divisions without direct authority. Ability to work effectively in a fully remote, globally distributed organization with excellent written and asynchronous communication skills. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $250,000 — $349,000 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: Canada; United States Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE Docker's Product-Led Growth (PLG) team owns turning product usage into revenue across the full Platform: the Container business (Docker Desktop, Docker Hub, Docker Build Cloud, Docker Scout) and the AI business (Sandboxes, AI Governance, Model Runner, MCP Toolkit, MCP Catalog). Lifecycle marketing is one of the fastest-scaling parts of that team: it already owns user and admin nurtures, renewal automation, and first-touch outreach for PQLs and inbound leads, running against a marketable base in the tens of millions. As Senior Lifecycle Marketer, you'll report directly to the VP of PLG and partner closely with our existing lifecycle marketing lead. You'll take ownership of assigned products, audiences, and lifecycle stages, with real input into shaping the approach for what you own, not just shipping someone else's plan, and you'll help turn a fast-growing list of priorities into a structured, scalable lifecycle engine. _______________________________________________________________________ WHAT MAKES SOMEONE SUCCESSFUL IN THIS ROLE - Lifecycle Fluency: You think in full user journeys, not campaigns. You've done lifecycle marketing specifically, not just growth or demand gen, and you know how nurture, activation, retention, and renewal connect across a product's full lifecycle. - Builder's Mindset: You'd rather own a program end to end, strategy, build, QA, and send, than hand pieces of it off. You bring structure to ambiguity: turning a fast-growing list of priorities into themes, a build queue, and a sequenced roadmap. - Audience & Signal Validation: You know how to validate an audience and its underlying signal before it ships: spot-checking record-level data, sanity-checking targeting logic, and catching a bad segment before it reaches users. You don't need to write SQL yourself, but you can work directly with data teams to confirm a list is right. - Cross-Functional Operator: You operate well across marketing, sales (BDR and renewals), data, and design/agency partners, and you know how to keep programs moving even when you don't own every dependency. - Marketing Automation Execution: You've personally built campaigns in Marketo or an equivalent platform, not just briefed them: audience builds, suppressions and contact governance, pre-send QA and live proofs, and launch monitoring, including troubleshooting a broken data sync in the moment. - Technical Translation: You can take a technical product or a raw usage signal, a feature adoption event, a usage threshold, a new capability, and turn it into messaging that reads credible to a developer or admin, not generic marketing copy. _______________________________________________________________________ RESPONSIBILITIES - Build the Lifecycle Engine: Own and build lifecycle campaigns (email and in-product messaging) across Docker's Container and AI Platform products, including Sandboxes and AI Governance, for both end users and admins. - Scale Programmatic Sends: Design and run large-scale programmatic sends, such as recurring account health checks, to a base in the tens of millions, working within the team's marketing automation stack (currently Marketo and Mailgun; expect a platform transition in the next 6–12 months). - Automate Lead and Renewal Motions: Stand up and run automated first-touch flows for PQLs and inbound leads, in partnership with BDR and renewals stakeholders. - Validate Audiences & Signals: Partner with data and growth engineering to pull the usage signals campaigns depend on (Snowflake and internal data tools), and validate that an audience and its underlying signal are correct before every send. - Manage Suppressions & Contact Governance: Own suppression lists and contact governance rules so campaigns stay compliant and don't over-message or reach the wrong audience. - QA, Launch Monitoring & Troubleshooting: Run pre-send QA and live proofs on every campaign, monitor launches as they go out, and troubleshoot issues in real time, including broken data syncs. - Translate Signals into Messaging: Turn technical product usage and adoption signals into messaging that reads credible and useful to developers and admins, not generic marketing copy. - Shape and Sequence Strategy: Take a fast-growing list of priorities and turn it into a concrete build queue: itemize the work, sequence it, and flag capacity or dependency issues early. - Coordinate Design & Agency Partners: Work with design and agency partners to keep campaign quality and turnaround on track. - Operationalize Reporting: Own naming, tracking, and reporting on programs so the rest of the team has visibility into what's live, what's next, and what it's driving. _______________________________________________________________________ QUALIFICATIONS - Lifecycle Marketing Experience: A background specifically in lifecycle marketing, not pure growth or demand gen, ideally inside a PLG or self-serve motion. - Proven Program Ownership: A track record of owning campaigns end to end (strategy, build, QA, send) and shipping programs that moved a real metric: activation, retention, or renewal conversion. - Marketing Automation Build Experience: Hands-on build experience in Marketo or an equivalent marketing automation platform: audience builds, program/campaign setup, suppressions and contact governance, pre-send QA and live proofs, and launch monitoring. - Data & Targeting Validation: Comfortable working directly with data teams to validate record-level data and targeting logic, for example auditing who's actually in a segment or spot-checking a list against expectations. Writing SQL yourself is a plus, not a requirement. - Technical-to-Message Translation: A track record of turning a technical product or a raw usage signal into messaging that reads credible to a developer or admin audience, not generic marketing copy. - Technical Familiarity: Comfort navigating developer ecosystems, cloud infrastructure, or complex multi-product software platforms. - Independent Ownership: Senior-level judgment and ownership as an individual contributor: you can run with ambiguity and drive a program without every step spelled out, and you collaborate well with another senior peer on the team. _______________________________________________________________________ WHAT TO EXPECT FIRST 30 DAYS - Immerse & Align: Get up to speed on Docker's PLG motion, product surface area (Container and AI), and the programs lifecycle already owns. Build a working relationship with data, BDR, renewals, and design/agency partners. - Program & Tooling Audit: Audit the current state of user and admin nurtures, renewal automation, and PQL/lead outreach, and get familiar with the Marketo/Mailgun stack and its upcoming transition. - Roadmap Calibration: Work with the lifecycle team to turn the current priority list into themes, a build queue, and a sequenced roadmap. FIRST 90 DAYS - Ship Owned Campaigns: Take ownership of at least one full program, such as an admin nurture flow or a PQL first-touch sequence, from build through send. - Contribute to Renewal Automation: Stand up a first version of automated renewal outreach in partnership with the renewals team. - Build the Reporting Cadence: Put in place naming, tracking, and reporting so the team has clear visibility into what's live and what it's driving. ONE YEAR OUTLOOK - Own a Mature Program Set: Own a mature, scaled set of lifecycle programs across your assigned products, audiences, and lifecycle stages. - Prove Impact: Show measurable lift in activation, retention, or renewal conversion tied directly to your programs. - Scale the Function: Help lifecycle marketing operate as a predictable, automated engine rather than a set of one-off campaigns, as scope keeps expanding across the Platform. Visa sponsorship: Not available for this role. _______________________________________________________________________   COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. Canada: CA$160,300– CA$229,000 base United States: $115,500 – $165,000 base ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

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 Design at Anthropic sits at the intersection of craft, research, and product intuition. We're a small team working on products that millions of people use daily—and on interactions that don't have established conventions yet. Our work shapes how people experience AI: whether Claude feels like a tool or a collaborator, whether it earns trust or erodes it. We partner closely with engineers and researchers, often designing around capabilities that are emerging in real-time. That means staying close to the models, prototyping rapidly, and being comfortable with ambiguity. We're looking for designers who ship fast and stay in motion—people who would rather get something in front of users this week than perfect it for a month. You're excited to question fundamental UI assumptions and invent patterns that feel native to AI, and you're already using tools like Claude Code to extend what you can build. You pay attention to where model capabilities are heading, not just what Claude can do today, and you find ways to keep caring about the pixels, the copy, and the edge cases while shipping quickly. Key responsibilities Collaborate with product managers, engineers, AI researchers and other stakeholders to define product vision, strategy and roadmaps, and play an active role in shipping. Understand the technical architecture of our products and define primitives for new capabilities. Define feature areas with exceptional attention to detail and polish, identifying opportunities to improve quality and consistency of broader flows Craft beautiful, polished, and delightful user interfaces that build trust and showcase the power of our AI technology Comfortable in code, design, prototypes, and learning new ways to communicate ideas and concepts Find creative ways to ship high-quality work in a fast-paced, often ambiguous, resource-constrained startup environment Minimum qualifications Experience designing and shipping complex workflows, enterprise/B2B SaaS, developer tools, or API products end-to-end Proven track record of executing end-to-end on large and complex products, or a series of products, in ambiguous environments A portfolio demonstrating user-centered design thinking and polished UI craftsmanship Proficiency with modern design and prototyping tools, such as Figma Experience using AI tools such as Claude Code as a creative partner in your own design practice Excellent collaboration and communication skills to work effectively with cross-functional teams and influence without authority Preferred qualifications Experience prototyping with front-end code (e.g., HTML/CSS/JS) Passion for crafting scaled, highly impactful, safe and beneficial artificial intelligence technologies to enable new possibilities 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: $305,000 — $460,000 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: Hamburg Workplace: Hybrid Every great app out there deserves to be connected with the right users and the right revenue streams. And adjoe will give this to them. adjoe is redefining the future of mobile ads. Powered by advanced AI, first-party data and world-class engineers, we’ve perfected the offerwall experience for monetizing and scaling app publishers with solutions like Playtime and Arcade – now the fastest growing rewarded advertising channel globally – driving incremental engagement, retention, and revenue. At the same time, we’re breaking into programmatic advertising with the intelligent bidding system of adjoe Ads. Together, this ecosystem connects app developers to over 600 million users worldwide for scalable growth. Backed by a $100 million investment from Bertelsmann and operating from offices in Hamburg, Boston, Singapore, and Tokyo, adjoe is defining the next stages of app and ad experience – right now. Join us. Meet Your Team: Supply Growth At adjoe, we turn app publishers' potential into proven revenue. Our Supply Growth team combines adjoe’s deep technical expertise with strategic insight to optimize every aspect of creating engaging user experiences that drive monetization. We understand the delicate balance between user engagement and revenue generation, optimizing ad placements for visibility while ensuring a seamless app experience. Our publishers see concrete results: higher ARPDAU, improved retention metrics, and stronger overall user satisfaction and monetization performance. Your Mission & Who We Are Looking For - Portfolio Growth & Monetization: You bring 3+ years of experience in AdTech, mobile advertising, or digital marketing to manage and expand a portfolio of app publisher partners, actively identifying upselling and optimization opportunities to exceed growth, retention, and revenue targets. - Analytical KPI Optimization: You possess a deep understanding of core industry metrics—including CPI, CPM, CPC, ARPDAU, and CTR—and will analyze partner performance data to spot trends, troubleshoot issues, and implement concrete adjustments that improve retention and ARPDAU. - Strategic Partner Engagement: You will build long-term publisher relationships through daily communication via Slack, email, and video calls, utilizing Google Workspace (specifically Sheets and Slides) to construct and deliver data-driven performance reports and Quarterly Business Reviews (QBRs) to external and internal stakeholders. - Cross-Functional Technical Advocacy: You will gather complex partner feedback and translate market insights into actionable technical requirements, collaborating directly with Product, Tech, and Business teams to prioritize feature requests and resolve integration blockers. - Proactive Ownership in Fast-Paced Environments: You thrive in an agile, rapidly changing ecosystem, taking full end-to-end accountability for portfolio performance by independently driving growth initiatives rather than waiting for direction. 🌎 We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team. What’s in It for You? At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day. - Go Big. Own projects with impact on 770M users and push adtech boundaries. - Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum. - Be Direct. Solve problems openly and collaborate across teams. - Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other. - Have Fun. Celebrate wins, enjoy daily victories, and bring your energy. Skip writing cover letters. Tell us about your most passionate personal project, your desired salary, and your earliest possible start date. We are looking forward to your application! We welcome applications from people who will contribute to the diversity of our Company. We welcome applications from people who will contribute to the diversity of our company.

Location: Paris Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE Cybersecurity is one of the areas where AI could do the most good — and one where the capability must be built with particular care. As a Research Engineer on this track, you'll push our models' capabilities in vulnerability discovery and remediation, security analysis, incident response, and across the offensive-to-defensive spectrum of cybersecurity, and it will be your job to develop that ability deliberately and safely. The work sits at the meeting point of research and engineering: you'll devise new approaches and be the one to implement them. Concretely, that means designing and building RL environments that reproduce realistic security scenarios, pipelines that generate synthetic training instances at scale, and experiments and evaluations that show what our models can actually do. Your results feed directly into the production training runs that shape our frontier models, in close collaboration with Mistral's researchers, engineers, and security specialists. Security specialists and ML engineers are both welcome here — what matters is that you can hold your own in both worlds, and are eager to go deeper on the one you know less. WHAT YOU WILL DO - Design and implement RL environments simulating cybersecurity scenarios. - Build the pipelines and infrastructure that generate synthetic cybersecurity training instances at scale — thousands of scenarios, not one hand-crafted exercise. - Conduct experiments and evaluations of model capabilities on these environments, from quick prototypes to controlled benchmark runs. - Own the infrastructure behind the environments: containers, sandboxes, VMs, cloud deployments, and orchestration (Kubernetes), all managed as code. - Partner with researchers and security specialists across Mistral, distilling their domain expertise into reproducible environments and datasets. - Write clear, efficient code in Python and enforce strong software-design practices: testing, code review, CI/CD. WHAT WE'RE LOOKING FOR - Hands-on expertise in offensive and/or defensive cybersecurity: vulnerability analysis, web/network/cloud security, secure coding practices, and SOC. - Strong software engineering skills: clean, reliable, well-tested code — not just exploit scripts. - Fluency in Python plus comfort reading lower-level languages (C/C++) for vulnerability analysis. - DevOps experience: Docker, Kubernetes, cloud deployments, sandboxed or simulated environments. - A pragmatic research-to-engineering mindset: ship a working first version, then refine and scale it. - Working knowledge of RL techniques and LLM training methodologies, or strong motivation to develop it. - Self-starter, low-ego, collaborative — comfortable working across research and engineering. NICE-TO-HAVES - CTF, cyber-range, or bug-bounty experience — as a player, challenge author, or platform builder. - A research background in cybersecurity, academic or industrial, or in another experimental discipline. - Prior experience building RL environments or large-scale ML training infrastructure. - Relevant open-source contributions and projects. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Hamburg Workplace: Hybrid Every great app out there deserves to be connected with the right users and the right revenue streams. And adjoe will give this to them. adjoe is redefining the future of mobile ads. Powered by advanced AI, first-party data and world-class engineers, we’ve perfected the offerwall experience for monetizing and scaling app publishers with solutions like Playtime and Arcade – now the fastest growing rewarded advertising channel globally – driving incremental engagement, retention, and revenue. At the same time, we’re breaking into programmatic advertising with the intelligent bidding system of adjoe Ads. Together, this ecosystem connects app developers to over 600 million users worldwide for scalable growth. Backed by a $100 million investment from Bertelsmann and operating from offices in Hamburg, Boston, Singapore, and Tokyo, adjoe is defining the next stages of app and ad experience – right now. Join us. Meet Your Team: Supply Growth At adjoe, we turn app publishers' potential into proven revenue. Our Supply Growth team combines adjoe’s deep technical expertise with strategic insight to optimize every aspect of creating engaging user experiences that drive monetization. We understand the delicate balance between user engagement and revenue generation, optimizing ad placements for visibility while ensuring a seamless app experience. Our publishers see concrete results: higher ARPDAU, improved retention metrics, and stronger overall user satisfaction and monetization performance. Your Mission & Who We Are Looking For - Data-Driven Revenue Optimization: You will analyze key monetization performance metrics (CPI, CPM, CPC, ARPDAU, and CTR) across your portfolio of app publishers to identify trends, uncover correlations, and make data-backed adjustments that maximize partner revenue and adjoe’s bottom line. - Proactive Portfolio Ownership: You will manage and nurture existing app publisher relationships through daily communication across Slack, email, and calls, serving as their primary contact to drive ongoing engagement and long-term account growth. - Technical Advocacy & Troubleshooting: You will gather detailed partner requirements and lead internal technical troubleshooting, translating publisher feedback into prioritized action items across cross-functional teams to keep integrations running seamlessly. - Operational & CRM Discipline: You will systematically track account activities, manage publisher pipelines, and maintain operational visibility using Salesforce, Jira, and internal dashboards to ensure zero drop-off in partner management. - Strategic Partner Reporting: You will prepare data-rich reports, presentations, and Quarterly Business Reviews (QBRs) using Google Suite and Google Slides to demonstrate clear ROI, elevate monetization strategies, and secure executive-level alignment with publishers. - Fast-Paced Execution: You will operate with high autonomy and a hands-on mindset in a rapidly evolving adtech environment, balancing competing priorities while maintaining a strict focus on output and revenue-generating activities. What’s in It for You? At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day. - Go Big. Own projects with impact on 770M users and push adtech boundaries. - Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum. - Be Direct. Solve problems openly and collaborate across teams. - Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other. - Have Fun. Celebrate wins, enjoy daily victories, and bring your energy. Skip writing cover letters. Tell us about your most passionate personal project, your desired salary, and your earliest possible start date. We are looking forward to your application! We welcome applications from people who will contribute to the diversity of our Company. We welcome applications from people who will contribute to the diversity of our company.

Location: Philippines; Indonesia; Thailand Workplace: fully We're Osome - entrepreneurs are society's problem solvers, and we build the tools that let them focus on solving problems instead of admin. We're looking for a Lifecycle Marketing Manager to backfill this role and take ownership of how leads move from first touch to closed revenue. As Osome is in an accelerated phase of growth, the scope of this role has evolved since it was first created. The business needs someone who can build and own the full lifecycle: campaign strategy in HubSpot, funnel optimization across every stage, and developing a lead progression model. The role also extends into running demand-generation campaigns, including webinars, for a B2B audience. How we will measure success: Funnel Conversion: Own nurture programs and improve conversion rate stage-over-stage across the funnel through targeted lifecycle campaigns and experiments. Lead Progression: Stand up a lead progression/ scoring model that Sales trusts and actively uses to prioritize outreach. Campaign Pipeline: Contribute qualified pipeline through demand-generation campaigns, including webinars, run in a B2B environment. Funnel Health: Reduce friction and drop-off at key funnel stages, identified through data and fixed through lifecycle-stage-specific messaging. What does the role do on a day-to-day basis: Lifecycle ownership: Own lifecycle marketing end-to-end in HubSpot — designing and building nurture tracks, drip campaigns, and audience segments that move leads through every stage, from first touch to customer. Ad-hoc email support: Support Marketing, Sales, and CX with ad-hoc email requests as they come up, outside the core lifecycle programs. Funnel optimization: Continuously map how leads flow stage to stage, identify drop-off points, and run experiments to lift conversion at each stage. Lead progression: Build, maintain, and refine a lead progression/ scoring model - defining the behavioral and firmographic signals that indicate sales-readiness, and working with Sales to keep the model aligned to what actually converts. Demand generation: Plan and run demand-generation campaigns on owned channels - including webinars, from topic and speaker selection through promotion, registration, follow-up, and conversion to pipeline - as part of the broader lifecycle and funnel work, in a B2B context. Marketing Ops partnership: Work closely with the Marketing Operations team on HubSpot workflows - you won't be building every lead-routing and scoring workflow yourself, but you'll need a deep, inside-out understanding of how they work so you can shape requirements, troubleshoot issues, and partner effectively with Ops on what gets built. Cross-functional alignment: Liaise with the Global marketing team (content, analytics, product) to align technical implementation of lifecycle and funnel initiatives, and partner with Sales and RevOps to ensure lead handoff, scoring thresholds, and lifecycle stages are consistently defined and tracked in the CRM. Reporting: Track and report on funnel and campaign performance (open, click-through, conversion, and stage-to-stage conversion rates), turning results into concrete optimization plans. Required Experience: 4-6 years of experience in a lifecycle/email marketing or marketing automation role, preferably in a SaaS or tech environment. Proven, hands-on experience building lifecycle marketing programs in HubSpot. Track record of funnel optimization work with measurable conversion improvements. Experience building or working closely with a lead-scoring mechanism. Experience running B2B marketing campaigns, webinars among them, as part of a broader marketing remit. Our Benefits Multi-cultural environment to enhance your global perspective. Learning opportunities and mentorship from peers and leaders. Remote working arrangement An agile working model focused on goals and performance. Equal Opportunity Statement At OSOME, creating a culture where individuals of all backgrounds feel comfortable really matters. Everyone who applies will receive fair consideration for employment. We do not discriminate based upon race, colour, religion, sex, sexual orientation, age, marital status, gender identity, national origin, disability, or any other applicable legally protected characteristics in the location in which the candidate is applying. We want to ensure that we represent the diversity of talent in the society we live in today. If you have any accessibility requirements that would make you more comfortable during the application and interview process, please let us know so that we can support you.

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 Claude is available to enterprises through Microsoft Foundry, and the Microsoft partnership has become one of our most important paths to market. Many of the largest enterprises in financial services, healthcare and life sciences, and the public sector buy Microsoft first, and we want Claude to be the obvious choice when they do. As Partner Manager for Microsoft Co-Sell, you will turn that partnership into pipeline and closed revenue. You will build and run joint sales plays with Microsoft's field organization, connect Anthropic account executives with their Microsoft counterparts on shared target accounts, and make sure deals that start in a co-sell conversation actually close through Azure Marketplace. You will own your work end to end, from the details of a single stuck deal to the executive readout on how the partnership is performing. Key responsibilities Own the co-sell engine day to day: design joint sales plays with Microsoft around the strongest enterprise use cases, run account mapping with Microsoft sellers, and turn introductions into working groups and joint opportunities that show up as pipeline Keep deals moving through Azure Marketplace, including private offers, billing setup, and partner attribution; track every opportunity through that process, know where it is stuck and who needs to act, and work with both sides until it closes Run the regular pipeline and escalation rhythm with Microsoft Give Anthropic and Microsoft leaders a clear view of what is working and what is blocked Bring field insight back to our product and go-to-market teams Own at least one major joint initiative with Microsoft, such as a flagship event, a product workstream, or deal operations Minimum qualifications Experience owning a revenue or pipeline number through a partner or co-sell motion, with results you can point to Working knowledge of how enterprise deals transact through a cloud marketplace, including hands-on experience unblocking stuck deals Strong attention to detail and operational rigor, with the ability to turn that detail into a clear, concise story for executives A record of taking full ownership of your work: closing loops and keeping stakeholders informed proactively Ability to keep a stalled deal or program moving through repeated blockers until it is resolved Ability to build trust across a large, matrixed partner organization, with field sellers and their leaders alike Preferred qualifications Experience selling or partnering around AI, ML, or developer platform products Direct experience with Microsoft's partner ecosystem, such as Partner Center, Azure Marketplace, and the co-sell program Experience selling into financial services, healthcare and life sciences, or the public sector 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: $215,000 — $300,000 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 | Washington, DC 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 We're hiring a strategist to join the Policy Campaigns team within Anthropic's Public Policy team. The Policy Campaigns team turns the company's policy priorities into active campaigns: research and polling, messaging, coalitions, paid media, and external execution. We're hiring a strategist to develop and execute paid media campaign strategy, manage agencies, and measure the success of our advocacy campaigns in the US and in priority markets abroad. This is a strategy and program management role. You'll decide what a campaign needs to accomplish, who needs to hear from us, which messages and tactics will move them, and then implement accordingly. Anthropic works on many policy issues at once, across many markets, and you'll need to understand the full set of issues and find the right cross-cutting approaches to advance our goals. You'll direct the agencies that produce and place the work, and bring Policy, Communications, Marketing, Public Affairs, and Legal to agreement on tight legislative timelines. The role also carries a substantial project management load. You'll run several campaigns at once, across time zones and agencies, and keep each one on schedule and on budget. You'll report to the Head of Policy Campaigns. Key responsibilities Design paid and digital campaign strategies for legislative and policy goals, including objectives, audiences, messaging, tactics, phasing, and budget Develop campaign messaging and tactics with the Campaigns team, executives, Public Affairs, and Communications, and make sure paid media carries the core message Spot where a campaign could conflict with Anthropic's other policy, commercial, or international priorities, and resolve those tensions before launch Direct creative and media-buying agencies: set strategy and briefs, scopes and budgets, hold timelines, and hold the work to a high standard Run several campaigns at once across time zones and agencies: own the timelines, workplans, budgets, and status reporting, and keep partners in the US and abroad aligned Build rapid response capabilities with Policy, Marketing, Legal, and Communications so campaigns can respond quickly in changing environments Set success measures before launch, report results plainly, and adjust strategy based on what works Work cross-functionally to find the stories and moments that make policy arguments concrete for policymakers and opinion formers Minimum qualifications Experience running digital content and paid media for a corporate affairs team, political campaign, advocacy organization, public affairs firm, or issue campaign, including owning a media budget Experience managing creative and media-buying agencies, including briefs, scopes, budgets, and performance reviews Experience running campaigns aimed at policymakers, key opinion formers, or other influential audiences Experience managing several campaigns or projects at once, with multiple agencies and stakeholders in different time zones Experience building campaign reporting in spreadsheets or dashboards Preferred qualifications Experience managing state or federal legislative campaigns Experience running campaigns inside a large organization or coalition with competing priorities Working knowledge of AI safety and technology policy issues Experience running campaigns in markets outside the US Hands-on familiarity with ad platforms and targeting, such as Meta, LinkedIn, and programmatic buying The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $265,000 — $295,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote - United States Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: Video is where multimodal models are weakest and hardest to grade. Temporal reasoning, long-form understanding, grounding events in time, and holding audio, video, and text together do not fall out of image benchmarks — and the evaluations for them are still immature. Closing that gap is gated as much by how we design data and evaluation as by architecture. Innodata builds that data and those evaluations for the customers and frontier labs advancing video and multimodal models, and we are hiring a Research Scientist to own the science behind it. You will partner directly with the customers and frontier labs building video understanding, video-language, and video-generation models, as interested in the data behind them as in the models themselves. Video spans two model families judged in completely different ways: models that understand video — answering questions, localizing events, grounding language in time — where the question is whether the answer is correct; and models that generate it, where fidelity, temporal coherence, and physical plausibility matter and no automatic metric is settled. You own the evaluation science for both, and knowing when model-based scoring can stand in for a human versus when it can't. Your conclusions shape what our partners measure and collect next. What You’ll Own: You will define how Innodata designs, structures, and evaluates video data for video and multimodal models, and you will validate those choices experimentally. Concretely, you will: Translate the requirements of video and multimodal models — video understanding, temporal and event localization, action recognition, long-form video, video-language models, video generation, cross-modal reasoning, and multimodal retrieval and grounding — into concrete data specifications: modalities, annotation schemas, sampling, and evaluation criteria. Build evaluation methodology for video understanding — temporal grounding accuracy, long-context and long-horizon reasoning, and dynamic multi-turn, cross-modal, and retrieval-and-grounding evaluation — clear about when model-based scoring is trustworthy and when a human is needed. Build evaluation methodology for video generation — fidelity, temporal coherence, and physical plausibility, including generative video used as a world model — the regime where automatic metrics are weakest and human judgment matters most. Decide how existing and incoming video should be structured, enriched, and sampled to extract the most model value from it, including from messy, domain-specific footage. Run experiments that prove data decisions matter: fine-tune and evaluate models on Innodata data, with ablations tying specific data choices to measurable improvement. Design adversarial and stumping evaluations that surface where video and multimodal systems fail, and turn those failures into better data. Publish. Turn what you learn into benchmarks, methodology, and papers that advance the field and earn the trust of the customers and frontier labs we partner with. Work with annotation teams, subject-matter experts, and the synthetic-data pipeline to turn specifications into operational collection and labeling plans. You’ll Thrive in This Role If You Have: Roughly 5+ years of hands-on industry experience in video understanding or multimodal ML. We weight practical experience over formal credentials; a PhD with a compelling, current research agenda can offset the lower end. A Bachelor's degree in computer science, electrical engineering, or a related technical or quantitative field is required; an advanced degree (MS or PhD) in a relevant field is preferred. Trained and evaluated video or multimodal models yourself, with strong PyTorch fundamentals. Fluency in the formats and tooling video work runs on: ffmpeg and decord pipelines, temporal and COCO-style annotation, WebDataset, Parquet and Arrow, and HuggingFace datasets. Experience fine-tuning large video or vision-language models with the modern toolchain (HuggingFace transformers, PEFT, efficient inference), and with long-form video, streaming, temporal segmentation, or synthetic video generation. A way of thinking in datasets and benchmarks: you have built evaluation sets, calibrated difficulty, and argued about what makes video data good for a given objective. A track record the field recognizes: first-author publications or strong open-source contributions at venues such as CVPR, ICCV, ECCV, NeurIPS, or ICLR. The ability to work directly with the research scientists at the customers and frontier labs we partner with, and to explain data and modeling decisions clearly to both expert and non-expert audiences, backed by a rigorous, reproducible approach to experiments and documentation. Bonus: interest or hands-on experience in responsible-AI evaluation and red-teaming — safety and robustness testing for video and multimodal systems. The expected salary range for this position is $160,000 - $185,000 p/year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Location: Remote - United States Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: Where models actually differ now is robustness across accents, noise, and code-switching; speaker diarization; the naturalness of generated speech; and latency under streaming. Measuring those honestly, and building the data that trains for them, is gated as much by data and evaluation design as by architecture. Innodata builds that data and those evaluations for the customers and frontier labs advancing speech and audio models, and we are hiring a Research Scientist to own the science behind it. You will partner directly with the customers and frontier labs building ASR, text-to-speech, speech-to-speech and conversational voice, diarization, and audio-language models, as interested in the data behind them as in the models themselves. Your work is judgment: which conditions and languages a benchmark must cover to be honest, what a transcription convention should be for a given objective, and when an automated metric can be trusted versus when a human ear is required. You will also partner closely with our transcription and linguistics lead, whose standards directly shape what the models learn. What You’ll Own: You will define how Innodata designs, structures, and evaluates audio data for speech and audio models, and you will validate those choices experimentally. Concretely, you will: Translate the requirements of speech and audio models — ASR, text-to-speech and speech generation, speech-to-speech and conversational voice, speaker diarization and verification, audio-language models, and streaming systems — into concrete data specifications: modalities, transcription and annotation schemas, sampling, and evaluation criteria. Build evaluation methodology that goes past word error rate — semantic accuracy, robustness to noise and accent, code-switching, diarization error rate (DER), naturalness and intelligibility of generated speech, and streaming latency — and know when automated metrics hold and when they don't. Decide how existing and incoming audio should be structured, enriched, and sampled for coverage that fits the model objective — across languages, accents, and acoustic conditions (studio, real-world, telephonic), speaker demographics, emotional and paralinguistic range, scripted versus spontaneous speech, and single- versus multi-speaker settings, including low-resource and code-switched speech. Partner with the transcription and linguistics lead to turn model objectives into transcription specifications, and to quantify how transcription conventions and quality move ASR and speech-model results. Partner with the audio solutions and engineering team so the audio we collect is built for the model objective: you specify what good data and evaluation require, and they scope programs with customers and capture audio to spec. Run experiments that prove data decisions matter: fine-tune and evaluate models on Innodata data, with ablations tying specific data choices to measurable improvement. Design adversarial and stumping evaluations — noisy, accented, and adversarial audio — that surface where speech systems fail, and turn those failures into better data. Publish. Turn what you learn into benchmarks, methodology, and papers that advance the field and earn the trust of the customers and frontier labs we partner with. Work with annotation teams, subject-matter experts, and the synthetic- and augmented-audio pipeline to turn specifications into operational plans. You’ll Thrive in This Role If You Have: Roughly 5+ years of hands-on industry experience in speech or audio ML. We weight practical experience over formal credentials; a PhD with a compelling, current research agenda can offset the lower end. A Bachelor's degree in computer science, electrical engineering, or a related technical or quantitative field is required; an advanced degree (MS or PhD) in a relevant field is preferred. Trained and evaluated speech or audio models yourself — ASR, TTS, speech-to-speech, speaker, or audio-language models — with strong PyTorch fundamentals. Fluency in the toolchains and metrics speech work runs on: ESPnet, NeMo, SpeechBrain, or Kaldi, HuggingFace, forced alignment, and WER/CER and the metrics that go beyond them. Hands-on experience with multilingual, accented, dialectal, low-resource, or code-switched speech, and with synthetic or augmented audio (TTS pipelines, noise and room-response simulation). A way of thinking in datasets: you have built evaluation sets, reasoned about coverage across conditions, and argued about what makes speech data good for a given objective. A track record the field recognizes: first-author publications or strong open-source contributions at venues such as Interspeech, ICASSP, ASRU, SLT, or NeurIPS. The ability to work directly with the research scientists at the customers and frontier labs we partner with, and to explain data and modeling decisions clearly to both expert and non-expert audiences, backed by a rigorous, reproducible approach to experiments and documentation. Bonus: interest or hands-on experience in responsible-AI evaluation and red-teaming — for example spoofing and voice-cloning robustness, or bias across accents and languages. The expected salary range for this position is $160,000 - $185,000 p/year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Location: Remote - United States Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: Progress in physical AI is gated as much by data design as by model architecture. The best manipulation and locomotion policies, vision-language-action models, and world models are only as good as the trajectories, demonstrations, and environments they learn from — so the highest-leverage decisions are made long before a model trains: what to capture, what to synthesize, how to represent an action, and how to know whether any of it will transfer to a real robot. Innodata is building the data and evaluation practice behind the next generation of robotics foundation models, in direct partnership with the customers and frontier labs defining that frontier. We are hiring a Research Scientist to own the science of that data. You will partner directly with the customers and frontier labs building robot foundation models, as interested in the data those models learn from as in the models themselves. Your leverage is scientific judgment about data: deciding what is worth capturing in the real world versus generating in simulation, how to weight a training mix across embodiments and sensors, and how to measure whether a policy will hold up outside the lab. Your conclusions will shape what our partners collect next. What You’ll Own: You will define how Innodata designs, structures, and evaluates data for robot foundation models, and you will validate those choices experimentally. Concretely, you will: Translate the requirements of robotics foundation models — vision-language-action models, world models, and manipulation and locomotion policies — into concrete data specifications: modalities, action representations (tokenization, chunking, diffusion and flow-matching action experts), sampling, annotation schemas, and evaluation criteria. Decide what is worth capturing in the real world versus generating in simulation, and curate and weight training mixes across heterogeneous robot datasets that span different embodiments, action spaces, and sensor setups. Guide collection across capture modalities — motion capture, egocentric, exocentric, teleoperation, and multi-sensor — and across synthetic pipelines, so that what we produce maps cleanly to model needs rather than accumulating for its own sake. Build evaluation and benchmarking methodology that predicts real-world transfer — coverage, discriminative power, reliability, and sim-to-real fidelity — including world-model evaluation (rollout quality and action-conditioned prediction) and the domain-randomization and system-identification choices that close the sim-to-real gap. Run the experiments that prove it: fine-tune and evaluate foundation models on Innodata data, with data-quality ablations and scaling studies that demonstrate specific data decisions produce measurable model improvement. Design adversarial and long-horizon evaluations that surface where policies and world models break, and turn those failure modes into better data. Publish. Turn what you learn into benchmarks, methodology, and papers that advance the field and earn the trust of the customers and frontier labs we partner with. Collaborate with the capture lab, annotation teams, and the synthetic-data pipeline to turn specifications into operational collection and labeling plans. You’ll Thrive in This Role If You Have: Roughly 4+ years of hands-on industry experience in robot learning or robotics ML. We weight practical experience over formal credentials; because the field is young, a PhD with a compelling, current research agenda can offset the lower end, and we will also consider very senior candidates with the right background. A Bachelor's degree in computer science, electrical engineering, robotics, or a related technical field is required; an advanced degree (MS or PhD) in a relevant field is preferred. Trained and evaluated robot policies yourself — manipulation or locomotion via imitation learning or reinforcement learning — with strong PyTorch fundamentals. You build and measure models, you don't just call them. A way of thinking in datasets: you have curated, filtered, and weighted robot data across embodiments and sensors, and you have real opinions about what makes it good for a given objective. Fluency in robotics data formats and standards — the LeRobot dataset format, RLDS, and Open X-Embodiment — along with common motion and sensor formats. Hands-on experience with simulation and synthetic data — NVIDIA Isaac Sim, Isaac Lab, and Omniverse, or MuJoCo and comparable engines — including domain randomization, system identification, and sim-to-real transfer. Experience with teleoperation or egocentric data collection, and comfort adapting VLM backbones for control and fine-tuning large VLA models with the modern toolchain (HuggingFace transformers, PEFT). A track record the field recognizes: first-author publications or strong open-source contributions at venues such as CoRL, ICRA, IROS, RSS, or NeurIPS. The ability to work directly with the research scientists at the customers and frontier labs we partner with, and to explain data and modeling decisions clearly to both expert and non-expert audiences, backed by a rigorous, reproducible approach to experiments and documentation. Bonus: interest or hands-on experience in responsible-AI evaluation and red-teaming for embodied systems, for example safety and robustness testing. The expected salary range for this position is $160,000 - $185,000 p/year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Location: Remote - United States Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: As speech and audio models get better, the human role gets harder, not easier — it moves from producing transcripts to defining what a correct one is, adjudicating the cases models still get wrong, and designing the human-in-the-loop workflows that keep improving them. Innodata runs high-volume segmentation and transcription workflows for the customers and frontier labs building these models, and we are hiring a principal-level linguist to own the linguistic standards and quality behind that work — today, and as the workflows evolve alongside the models over the next two years. This is the applied-expert counterpart to our Speech & Audio Research Scientist. You set the standards the models are trained and measured against, and you understand the big picture: how different transcription and segmentation methods change what a model learns, and how that ripples into the speech and content-understanding systems our partners are building. You know the research and you know the tools — from IPA and acoustic analysis to forced alignment and the ASR engines our partners benchmark against — but your leverage is linguistic judgment and standard-setting at scale, not building models yourself. What You’ll Own: You will own the linguistic foundation of Innodata's segmentation and transcription work across languages, domains, and use cases. Concretely, you will: Define transcription and segmentation standards, style guides, and annotation conventions — verbatim and clean/intelligent verbatim, IPA and phonetic transcription, timestamping and boundary segmentation, speaker labeling and diarization labels, disfluencies and non-speech events, code-switching, and orthographic conventions. Establish and run the quality frameworks behind that work: rubrics, error taxonomies, adjudication processes, inter-annotator agreement, and human QA at scale. Own the quality lifecycle for transcription and segmentation deliverables end to end — pre-processing and normalization of incoming data, quality checks at the point of acceptance, post-processing and pre-delivery validation against spec, and report creation and packaging for delivery — partnering with delivery operations on execution at scale. Design the human-in-the-loop workflows themselves — deciding where human review, correction, and adjudication add the most value as ASR quality rises, so our experts spend their time on what the models still can't do rather than on what they already can. Handle the linguistically hard cases models fail on — accented and dialectal speech, low-resource and multilingual audio, overlapping speech, domain jargon (medical, legal, technical), and noisy acoustic conditions. Partner with the Speech & Audio Research Scientist to turn model objectives into transcription and segmentation specifications, and to work out how different transcription methods — verbatim versus clean, phonetic versus orthographic, and how audio is segmented and labeled — affect the training and evaluation of ASR, TTS, and speech and content-understanding models. Train, calibrate, and mentor expert transcribers and reviewers, and build the onboarding and calibration that keep quality consistent as the work scales. Represent Innodata's transcription and segmentation approach to the customers and frontier labs we partner with, and contribute to the methodology and best-practice documentation that make our work legible to their teams. You’ll Thrive in This Role If You Have: Substantial industry experience (typically 8+ years) in transcription, segmentation, and speech-data quality — enough that you have authored standards, not only followed them. This is a principal-level role, and we weight practical depth heavily. A Bachelor's degree in linguistics, phonetics, or computational linguistics, or a closely related field, is required — with a strong foundation in phonetics, phonology, and sociolinguistics so that IPA, prosody, disfluency, dialect, and register are native concepts. An advanced degree is preferred. A big-picture grasp of how transcription and segmentation choices flow downstream into modeling — how different methods change what speech and content-understanding models learn, and therefore which method fits which modeling objective. You can explain to a model builder why a transcription decision matters. Fluency in phonetic transcription and IPA, plus hands-on experience with acoustic and phonetic analysis of speech — spectrograms, formants, pitch and prosody, and segment boundaries — applied to real, messy speech data at scale (for example in Praat). Deep experience with audio segmentation and its conventions — utterance and turn boundaries, timestamping, and speaker and diarization labeling — across real-world audio. Hands-on fluency with the modern speech stack: Whisper and the commercial ASR engines your partners benchmark against (such as AssemblyAI, Deepgram, Rev, and Speechmatics), forced alignment (for example the Montreal Forced Aligner), and annotation tools such as ELAN. Comfort scripting for speech-data work — Python for batch processing, QA, and metrics such as inter-annotator agreement and WER, plus regular expressions and Praat scripting — enough to work fluently with data and pipelines without needing an engineer for every task. Practical data-management skills across the delivery lifecycle — pre-processing, acceptance-stage quality checks, post-processing, pre-delivery validation, and report creation and packaging — so deliverables leave the door correct, consistent, and well documented. Multilingual capability and hands-on experience with accented, dialectal, and code-switched speech; low-resource languages a strong plus. A point of view on how human-in-the-loop workflows should evolve as models improve — where humans stay in the loop, where they move up to adjudication and standard-setting, and how to measure the difference. Strong written and verbal communication, comfortable working directly with research scientists and interfacing with the customers and frontier labs we partner with. Bonus: responsible-AI considerations for speech, such as bias across accents and dialects and privacy and consent in voice data. The expected salary range for this position is $160,000 - $185,000 p/year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Location: Los Angeles, USA Technical Product Managers combine deep technical knowledge and experience with product leadership capabilities which are needed to enable Riot Games to deliver key products and experiences to make it better to be a player. You will develop and execute strategies on Riot's products and technologies while leading diverse teams to deliver creative solutions to our most difficult technical and experiential challenges. As a Principal Technical Product Manager for VALORANT Foundations, reporting to the Director of Technical Product Management for VALORANT, you’ll identify and lead the highest-impact opportunities across the platforms that make the game predictable to build, release and operate worldwide. Foundations serves VALORANT’s engineers, artists and designers through build and release pipelines, developer tools and workflows, engine capabilities and core backend services. Working with engineering leads, game teams and central technology partners, you’ll bring independent product judgment to ambiguous problems, build support for a clear direction, and lead delivery across teams without direct authority. Your success will be measured in faster development workflows, more predictable releases, and platforms that let VALORANT grow sustainably. Responsibilities: Define and align product strategy for critical, cross-cutting platform areas, prioritizing outcomes that create measurable value for developers and players Bring strategic structure and clarity to Foundations' hardest, most ambiguous initiatives so they're set up for long-term success Lead cross-functional teams through influence, bridging engineering reality and product requirements, and driving decisions to closure across the groups that own build and release pipelines, the developer inner loop and editor, engine capabilities, and core backend services, all without direct authority Serve as a strategic proxy for Foundations leadership, stepping in with autonomy to own high-stakes opportunities end to end Partner deeply with engineering leads to ensure platform solutions are robust, scalable, and seamlessly integrated into developer workflows Broker across the seam with central tech team partners, representing VALORANT's needs into shared platforms and negotiating what's owned where Translate empathy for internal developers into infrastructure and tooling that solves genuine pain points; champion data-informed decisions Champion AI-augmented ways of working: bring agentic tooling into the PM craft to compress cycle time and model what modern product management looks like for Foundations Required Qualifications: 8+ years of relevant experience in Technical Product Management or a related engineering/technical field Familiarity with the game development lifecycle: engines, art/build toolchains, live-ops workflows Proven ability to operate at a Principal level, navigating organizational complexity to drive outcomes without direct authority Strong technical background (CS degree or equivalent experience) sufficient to credibly debate tradeoffs with engineering leads Experience translating open-ended or ambiguous technical capabilities into concrete product roadmaps with defined milestones and success metrics Track record owning platform, developer-tools, or systems products with internal customers Experience integrating agentic AI tooling into the product-management craft, using agents to shorten the loop from insight to execution Desired Qualifications: Experience with developer experience / platform-as-a-product domains, including internal platforms, SDKs, or CI/CD tooling Experience operating across the studio/central-tech boundary, or in a shared-infrastructure org serving multiple teams Hands-on familiarity with Unreal Engine and the Unreal Editor, VALORANT's engine and the primary environment its developers work in For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role! Our Perks: Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules. We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match. Check out our benefits pages for more information. At Riot Games, we put players first . That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application. It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act. Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories: Safeguarding confidential and sensitive Company data Communication with others, including Rioters and third parties such as vendors, and/or players, including minors Accessing Company assets, secure digital systems, and networks Ensuring a safe interactive environment for players and other Rioters These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security.