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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 We are hiring a Strategic Sourcing lead to drive development and execution of procurement strategies to help scale Anthropic's Data Center electrical and mechanical Owner Furnished Equipment (OFE) footprint. In this role, you will own end-to-end sourcing strategies for critical electrical and mechanical infrastructure such as generators, switchgear, UPS systems, chillers, and cooling equipment. You will partner closely with engineering, demand planning, construction, and third parties to drive equipment availability, establish vendor relationships, and negotiate commercial agreements. As a sourcing lead focused on key Data Center equipment, you will play a critical role in helping Anthropic to achieve its ambitious scaling goals. Key responsibilities Drive commercial negotiations and Master Purchase Agreements for critical electrical and mechanical infrastructure such as generators, medium- and low-voltage switchgear, transformers, UPS systems, chillers, cooling towers, CRAHs, and pumps. Audit partner procurement schedules, ensure optimal allocation, and drive cost efficiency of supply in constrained markets. Implement frameworks for ensuring third-party data center partners and general contractors adhere to commercial equipment terms and technical specifications. Develop global inventory strategy including warehousing, third-party logistics, buffer stock, and distribution models to accelerate time to market and improve availability. Proactively monitor global supply chain volatility (e.g., lead times for transformers, generators, and switchgear) and execute contingency plans to avoid critical project delays. Translate construction and capacity roadmaps into equipment forecasts and procurement pipelines. Partner with Finance to optimize inventory and capital deployment strategy. Establish efficient return, repair, and replacement workflows with OEMs to restore failed equipment quickly. Negotiate warranty, startup/commissioning support, and spare parts terms, and track vendor performance Minimum qualifications Have 7+ years experience in supply chain management, sourcing, and procurement. Have a track record of developing processes for forecasting, planning, and managing data center electrical and mechanical equipment for build-out and/or operations. Are familiar with data center electrical and mechanical equipment (e.g., generators, switchgear, transformers, UPS, batteries, chillers, cooling towers, CRAHs/CRACs, pumps, CDUs). Possess a bachelor's degree in a relevant domain (e.g., electrical/mechanical engineering, construction management, supply chain) or equivalent practical experience. Preferred qualifications 10+ years experience in supply chain management, sourcing, and procurement. 5+ years experience in data center or critical environment infrastructure. Experience working with general contractors, MEP integrators, OEMs, and equipment distributors. Experience working on data center construction programs. Familiarity with liquid cooling equipment (CDUs, dry coolers, manifolds) and battery energy storage systems. Leadership and influencing skills. Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 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: Japan Workplace: remote Overview  Are you passionate about languages, writing, and quality evaluation? We are launching an exciting language evaluation project and are looking for Japanese-speaking experts to join our team.    What you will do:   Identify realistic search-related failures where an AI model provides inadequate responses. Create search queries, test them, document what went wrong, and write instructions and evaluation criteria for correct answers. Common issues: local relevance, source quality, outdated information, language mismatches, incomplete answers, and region-specific inapplicability. Testing multiple queries before finding failures is expected. This is a practical, execution-focused role. We value hands-on performance and consistency over advanced academic training. Candidates who prefer theoretical/research work may not find this role a good fit. Project Details:      - Start Date: ASAP     - Duration: Ongoing Project.     - Commitment: 20/hours week.     - Job Type: Freelance contract.     - Location: Japan, Remote     - Rate: $35-57.75 per hour.     Requirements:       - Research skills — ability to find and verify information from multiple sources; comfort navigating different websites, databases, and documentation     - Critical thinking — Can spot contradictions between sources, identify outdated information, and recognize when something doesn't apply to a specific locale/context     - Attention to detail — Can catch nuances in language, local variations (prices, regulations, requirements), and edge cases     - Problem-solving mindset — Comfortable iterating and testing when things don't work; doesn't get frustrated by trial-and-error     - Domain knowledge — Ideally someone with background in research, quality assurance, compliance, or similar work that requires precision and source verification     - Writing clarity — Can articulate instructions and rubrics clearly so others understand the logic behind their reasoning     - Locale knowledge — Deep familiarity with their specific locale (local regulations, business practices, cultural nuances) is valuable for spotting region-specific failures

Location: United States (Remote); Canada (Remote) Workplace: Remote ROLE SUMMARY Join our Builder Platform Team as a Senior Staff Software Engineer. Our mission is to empower a company of builders by delivering a frictionless, standardized, and governed platform for agents, workflows, and core engineering tools. We operate Temporal as customer zero: we partner directly with teams across the company to run their real work on the platform, measure the productivity it unlocks, and feed what we learn back into Temporal’s products and open-source frameworks our customers can adopt. This is a company-level technical leadership role spanning Agents & Workflows, AI Infrastructure, Developer Infrastructure, and Productivity Engineering. You will set the multi-year technical direction for the platform, align teams around clear architectural boundaries and standards, and lead major cross-functional initiatives from ambiguous opportunity through durable adoption and measurable impact. WHAT YOU’LL DO - Set and communicate a multi-year technical vision for the Builder Platform, translating company strategy into an executable portfolio across Agents & Workflows, AI Infrastructure, Developer Infrastructure, and Productivity Engineering. - Lead the architecture and evolution of our Agent Platform, the shared foundation teams across Temporal use to deploy, run, evaluate, govern, and improve their agents and agentic workflows. - Establish and operate our AI Infrastructure, the LLM and MCP gateways every agent and workflow at Temporal runs through, with guardrails, fallback, usage and cost controls, model rollout policies, and clear SLOs. - Implement AI Governance in partnership with Security, Legal, and IT, turning policy into practical controls, approved patterns, and auditability without creating unnecessary barriers. - Architect the agents and workflows that carry engineering work from issue to production and business work from trigger to outcome, and decide which patterns graduate into shared platform capabilities and which stay with the teams that own them. - Own the technical strategy for our Developer Infrastructure (Source Control and CI) and developer tools, including repository standards, access and ownership models, reusable workflows, and CI reliability and cost. - Partner with leaders across Engineering, Product, Sales, and G&A to identify where AI can accelerate work and improve outcomes, and prioritize those opportunities into a company-wide portfolio. - Standardize how Temporal adopts agents and agentic tooling (best practices, paved roads, and enablement), driving adoption across the organization through influence rather than mandate. - Define clear architectural and organizational boundaries across the platform (what is centralized, standardized as a paved road, federated to teams, purchased, or deliberately not built) and make the hard tradeoffs among speed, flexibility, reliability, security, cost, and long-term maintainability. - Measure the platform on outcomes (adoption, velocity, reliability, and cost), with feedback loops that quantify the productivity it unlocks and shape the portfolio. - Own our customer-zero strategy: turn what we learn into validated requirements for Temporal Cloud, the SDKs, and our Agent Harness, drive the feedback loop with product leadership, lead our open-source reference architecture for customer platform teams, and represent the strategy with customers, partners, and the broader technical community. - Develop senior technical leaders, create alignment among engineering leads and managers, and make teams more effective without relying on direct authority. - Participate in on-call rotation while leading systemic improvements that reduce operational burden, address risks before they become company-wide problems, and improve the internal user experience. WHAT YOU’LL BRING - Strong software engineering fundamentals and a track record of setting technical direction and delivering major platform initiatives across multiple engineering teams. - Experience leveraging modern agentic coding tools such as Codex and Claude Code, including defining company-wide best practices and driving adoption across the organization. - Proficiency in one or more programming languages commonly used at Temporal, such as Go, TypeScript/JavaScript, Python, or Java, with deep expertise in at least one relevant domain (developer infrastructure, distributed systems, AI platforms, or platform engineering) and proficiency across several others. - Experience building and operating internal platforms, developer infrastructure, or agent platforms adopted across a company. - Strong judgment in platform-boundary decisions (what to centralize, federate, standardize, buy, or deliberately avoid building) and in tradeoffs among speed, flexibility, reliability, security, cost, and long-term maintainability. - Demonstrated ability to influence engineering managers, senior individual contributors, Security, Legal, IT, Product, and business stakeholders, and to turn ambiguous company objectives into architecture, standards, roadmaps, and coordinated execution. - Experience defining outcome-oriented metrics for developer productivity or AI systems (adoption, reliability, quality, cost, and cycle time) and using them to steer a portfolio. - Clear written communication, including documentation and technical strategy that enable self-service and align teams across the company. - Experience establishing governance through paved roads rather than documentation or approval processes alone. - Evidence of making other technical leaders and teams more effective through mentorship, architectural clarity, and consensus building. NICE TO HAVES - Experience building internal agents and operating an agent platform. - Experience building and operating Temporal applications. - Experience defining or implementing AI governance, model-access infrastructure, or agent evaluation systems. - Experience managing GitHub configuration, policy, and workflows at organizational scale - Familiarity with developer productivity measurement frameworks such as SPACE and DORA metrics. Temporal Technologies is an Equal Opportunity Employer. Temporal Technologies does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need. We embrace and celebrate differences and diversity. Temporal is committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. If you need to request a reasonable accommodation, please let your Recruiter know so we can assist.

Location: New York, NY (HQ); San Francisco, CA Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT RAMP LABS Ramp Labs is Ramp's AI research group. We post-train models on finance work, build the environments and evals they learn from, and ship them into the products 70,000+ companies use to move money. We think the defensible part of an AI product is the loop: proprietary environments, evals that track what customers care about, and models trained against both. ABOUT THE ROLE Every model decision at Ramp Labs runs through a benchmark. Which model to route to. Whether a post-training run worked. Whether an agent is ready to post a corrective journal entry to a customer's ledger without a human in the loop. You'll own Ramp's benchmarking effort. You'll turn real finance work (expense policy review, invoice coding, month-end close, spreadsheet Q&A) into benchmarks and RL environments, build the graders, and tell the team what is actually improving. WHAT YOU’LL DO - Build benchmarks from real workflows: turn agent traces, customer edge cases and expert labels into versioned benchmark suites for long-horizon agents that run for hours across tools and systems, plus tool use, multi-step reasoning and financial judgment - Own the benchmarking effort: decide what we measure, run benchmark suites across models and agent versions, and report results the team makes decisions on - Design graders: rubrics, programmatic checks and llm-as-judge, calibrated against human agreement, with a clear view of where each one breaks - Close the loop with post-training: turn evals into reward functions and RL environments, and catch reward hacking and contamination before they ship - Publish external benchmarks and write-ups on how models perform at real finance work WHAT YOU NEED - Hands-on experience building LLM benchmarks or evals that people used to make real decisions - Strong Python and software engineering; your eval code is reproducible and fast - Statistical judgment: variance, confidence intervals, sample size, inter-rater agreement, and knowing when a delta is noise - Working knowledge of post-training (SFT, RL with verifiable rewards) and how evals feed into it - Comfort with SQL and large datasets; you'll work directly from production traces - Taste for what is worth measuring NICE-TO-HAVE - Industry experience on an eval, benchmarking or post-training team - Built RL environments or verifiers for agentic tasks - Published benchmark or evaluation research (NeurIPS Datasets & Benchmarks, ICML, ACL) - Built or contributed to eval frameworks (verifiers, lm-evaluation-harness, HELM or similar) - Familiarity with accounting, finance or other expert-domain work - Public work we can look at: a benchmark, an eval suite, a failure-analysis write-up BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Location: Oakland, California, United States About the Job: LaunchDarkly is hiring a Chief of Staff to report to the CEO and partner with the Executive Leadership Team (ELT) as the company continues to scale. This is a senior, individual contributor role for a strategic operator and trusted advisor who thrives at the intersection of strategy, execution, communication, and data. As Chief of Staff, you’ll help translate company strategy into action, shape executive-level planning and decision-making, and ensure leadership discussions are grounded in clear insights and high-quality materials. You’ll operate with significant autonomy, exercise wide latitude in how work gets done, and act as a thought partner to senior leaders across the organization. This role is ideal for someone with deep experience navigating complex, cross-functional environments and a strong executive presence who is excited to have broad influence without people management responsibilities. Responsibilities: Strategic Leadership & Cross-Functional Execution Partner with the CEO to drive company-wide strategic initiatives from conception through execution. Help align the Executive Leadership Team and broader organization around priorities, tradeoffs, and outcomes. Proactively identify risks, dependencies, and gaps across critical initiatives and surface insights to leadership. Act as connective tissue across executives and teams to ensure strategy translates into coordinated action. Operating Cadence & Company Planning Shape and support LaunchDarkly’s operating rhythm, including owning OKRs and leadership planning processes. Design and evolve planning frameworks that enable effective executive decision-making. Support annual and long-range planning cycles, synthesizing inputs and highlighting strategic implications. Executive & Company Communications Lead the preparation and refinement of executive-level materials, including Board meeting materials and ELT presentations.  Ensure executive content is clear, concise, decision-oriented, and aligned with company strategy. Data, Insights & Analysis Partner on executive dashboards and reporting, ensuring metrics are accurate, consistent, and actionable. Analyze and understand data to inform strategic decisions and evaluate proposed initiatives. Translate analysis into clear recommendations for senior leadership audiences. Executive Meetings & Offsites Design agendas and content for executive meetings and off-sites with a focus on alignment and outcomes. Capture key decisions, clarify next steps, and support follow-through across the organization. Qualifications: Typically requires a minimum of 15 years of related experience, preferably in senior-level roles involving strategy, operations, consulting, finance, product operations, or executive advisory work. Demonstrated success partnering closely with executive leaders and influencing at the highest levels of an organization. Exceptional written and verbal communication skills, with the ability to distill complexity into clear, compelling narratives. Strong analytical capabilities and comfort working with SaaS metrics and executive-level data. Ability to manage multiple, high-impact workstreams with sound judgment and prioritization. High degree of discretion, integrity, and emotional intelligence. Pay: Target pay ranges based on Geographic Zones* for Level 6: Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $ 240,600 - $330,700 ** Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $ 216,500 - $297,600 ** Zone 3: All other US locations - $ 204,500 - 281,100 ** All Zones Inclusive of 10% Bonus Target LaunchDarkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location. *Within the United States, our geographic pay zones are defined by counties surrounding major metropolitan areas. **Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary. About LaunchDarkly: Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations. The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by: Improving the velocity and stability of software releases, without the fear of end customer outages Delivering targeted experiences by easily personalizing features to customer cohorts Maximizing the business impact of every feature through the ability to experiment and optimize Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status. LD invites any applicant to review our written Affirmative Action Plan. To do so, contact People Ops at hr@launchdarkly.com . Do you need a disability accommodation? Fill out this accommodations request form and someone from our People Operations team will contact you for assistance. Your safety matters to us. To protect yourself from potential scams, LaunchDarkly recruiters will only contact you from @LaunchDarkly .com email addresses or via LinkedIn from "Verified Recruiter" accounts. Be cautious of emails from other domains.  Legitimate LaunchDarkly recruiters will never ask for money, fees, or banking information before making a job offer. LaunchDarkly will never make a job offer without conducting a formal interview process. Our interview process does not involve asking detailed questions by email. If you are ever unsure about a communication that you receive, don't click any links—visit Careers | LaunchDarkly directly for confirmed job openings and links to apply. Please notify us of any fraudulent representation by sending an email to careers@launchdarkly.com .

Location: United States, San Mateo, CA Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. How would you like to influence the most successful gaming platform of all time by validating the very technology our developers use to build extraordinary games? Role Summary: Sony Interactive Entertainment (PlayStation) is seeking a Software Development Engineer in Test (SDET) to provide hands-on engineering excellence across our SDK ecosystem. This role focuses on building tools and infrastructure for analyzing the quality of the PlayStation SDK and related technology. While this is the primary domain, there are opportunities to expand into 3D graphics, spatial audio, artificial intelligence, and the fully integrated PlayStation game development environment. We are looking for someone who wants to directly impact PlayStation technology by developing tools and automated systems that deeply analyze SDK components and platform capabilities. You will help strengthen and evolve our testing infrastructure, raise the technical bar for quality engineering, and drive confidence in every release. If you’re passionate about solving complex system-level challenges and influencing technology used by people around the world, we want to hear from you, come help us power the future of PlayStation! What You'll Be Doing: - Crafting and improving automated test cases, sample applications, testing tools and frameworks for SDK libraries and low level software (C++) - Build and improve test infrastructure using Python and Groovy to simplify building, testing, and demonstrating PlayStation® sample applications. - Monitor test infrastructure, analyze automation failures, improve reliability, and optimize runtime performance. - Partner closely with software production and offshore teams to compose robust test plans, validation strategies, and documentation. - Define scalable, maintainable automation and infrastructure patterns that support long-term platform growth. - Contribute to architectural discussions for test systems spanning C++, embedded firmware (C), and Python-based infrastructure. - Identify technical risks early and drive mitigation strategies to protect release confidence. What We're Looking For: - Excellent interpersonal skills, including presenting technical direction to both engineers and executives. - Strong programming proficiency in Python & C++, as well as PyTest and GTest frameworks. - Self-directed, committed to producing strong results, and passionate about high-quality automation. - Experience building, running, and debugging software in both Windows & Linux environments. - Deep understanding of automation trade-offs and architectural design decisions. Nice-to-Have: - Exposure to Android platform, including SDK, tooling and architecture - Prior experience with PlayStation SDK development is helpful. - Familiarity with Unity, Unreal Engine or other game engine technology. - Containerization technology such as Docker and Kubernetes. - Proven experience leading complex debugging efforts. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment. Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: London, England, United Kingdom About the Job: We are looking for an experienced Executive Assistant to support the VP EMEA Sales at LaunchDarkly. You will bring structure, judgement and pace to a demanding leadership agenda, helping the VP focus on customers, the sales organisation and the priorities that move the EMEA business forward. Executive support is the core of this role, representing approximately 80% of the remit. The remaining 20% focuses on the smooth running of the London office. You will anticipate needs, make sound decisions within agreed boundaries and keep commitments moving across countries, time zones and changing priorities. Responsibilities: Executive support (~80%) Calendar and priorities Own a complex, fast-changing diary across EMEA and global time zones, prioritising customer and partner meetings, leadership commitments, interviews and focus time, and resolving conflicts early. Prepare the VP for the day and week ahead with schedules, context, briefing materials and advance notice of decisions and deadlines. Escalate competing priorities with practical options. Sales leadership cadence Organise weekly leadership meetings, forecast calls, pipeline reviews, QBRs and planning sessions, coordinating agendas, pre-reads and contributions. Capture decisions and actions, track owners and deadlines, and follow up. Keep the leadership calendar aligned with sales milestones, quarter-end activity and company commitments. Communications and sensitive matters Draft and refine correspondence, meeting materials, presentations and team updates for the VP’s review, communicating professionally with senior colleagues, customers, partners and candidates. Handle confidential commercial and people information (leadership discussions, organisational changes, recruitment) with discretion, keeping careful records and sharing only with appropriate people. Recruitment, travel and events Partner with recruiters and hiring managers to schedule interviews across time zones, coordinate candidate communications and keep feedback and decisions moving. Arrange complex international travel (itineraries, transport, accommodation, meeting logistics), manage changes, and coordinate expenses and documentation. Deliver logistics for sales leadership offsites, regional team meetings and executive customer visits, including venues, suppliers, communications, materials and agreed budgets. London office management (~20%) Coordinate daily operations (supplies, meeting spaces, deliveries, visitors), keeping the office organised and welcoming. Liaise with building management, facilities and service providers to resolve issues; coordinate purchases, supplier invoices and spend tracking within agreed approvals. Support new starters and team gatherings with People, IT and other teams, flagging workplace concerns to the right owners and following through. Balance office needs against the VP’s priorities, raising conflicts early so executive support stays primary. Qualifications: 5+ years of EA experience, including at least 3 supporting a VP or C-suite executive in a fast-paced business. Experience managing complex diaries, international travel and competing priorities across countries and time zones. Strong written and verbal communication, with the ability to draft clear executive correspondence and work confidently with senior stakeholders. Excellent judgement, discretion and reliability with confidential people and commercial matters. A proactive, highly organised, detail-oriented approach: you anticipate needs and follow through without repeated prompting. Confidence coordinating recruitment, leadership meetings and events, staying calm and adaptable when plans change. Proficiency with calendar, email, presentation, document and collaboration tools, and quick to learn new systems. Preferred experience: SaaS or technology experience, ideally supporting a regional sales leader or other senior commercial executive. Familiarity with sales leadership rhythms: forecasting, pipeline reviews, QBRs and quarter-end demands. Experience coordinating office operations, suppliers or workplace logistics alongside a substantial executive support remit. About LaunchDarkly: Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations. The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by: Improving the velocity and stability of software releases, without the fear of end customer outages Delivering targeted experiences by easily personalizing features to customer cohorts Maximizing the business impact of every feature through the ability to experiment and optimize Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status. Do you need a disability accommodation? Fill out this accommodations request form and someone from our People Operations team will contact you for assistance. Your safety matters to us. To protect yourself from potential scams, LaunchDarkly recruiters will only contact you from @ launchdarkly.com email addresses or via LinkedIn from "Verified Recruiter" accounts. Be cautious of emails from other domains.  Legitimate LaunchDarkly recruiters will never ask for money, fees, or banking information before making a job offer. LaunchDarkly will never make a job offer without conducting a formal interview process. Our interview process does not involve asking detailed questions by email. If you are ever unsure about a communication that you receive, don't click any links—visit Careers | LaunchDarkly directly for confirmed job openings and links to apply. Please notify us of any fraudulent representation by sending an email to careers@launchdarkly.com .

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 Claude Frontier Academy is where organizations nominate their strongest people to build deep, hands-on skills with Claude. Backed by a $100 million commitment, Anthropic aims to train 10,000 Frontier Deployed Engineers by the end of 2027. The Academy’s first program, the Frontier Deployed Engineer (FDE) Residency, brings engineers from leading customers and partners together in cohorts, and more programs will follow. We’re looking for a Marketing Lead to make the Academy a name the market knows and a credential people are proud to earn. As the Academy’s first dedicated marketer, you’ll own how it shows up in the world. You’re a creative, versatile marketer who thinks in terms of brand and communications and also knows how to position, launch, and grow programs. You’ll turn each program launch into a major market moment, celebrate milestones like new cohorts and the first badges earned, and build a community of graduates who help tell the story. Because the Academy serves both partners and customers, this role will sit on our Partner Marketing team. You’ll work directly with partners and customers to secure their participation in announcements and bring them into our launch and amplification plans. You’ll help shape the Academy’s strategy and annual plan and represent marketing with senior leaders, while staying hands-on enough to write the first draft yourself. Partners and customers already engage with other Anthropic education and training programs, so you’ll be thoughtful about how the Academy fits alongside them. If you’ve built a branded program at a B2B technology company and want to do it again at a much bigger scale, this role is for you. Key responsibilities Own the marketing strategy and annual plan for Claude Frontier Academy and its programs, working with Academy leadership to set priorities and goals Build and maintain a calendar of market moments for the Academy and each program, including program launches, new cohorts, and badge milestones Lead launches end to end, from messaging and announcement drafts through legal and executive review, launch-day execution and post-launch amplification Partner with Communications on press releases and announcements, including sourcing customer and partner quotes and securing approval to use their names Align early with Partnerships, Communications, and Account Teams on which customers and partners are named in each announcement, who gets a heads-up before it goes live, and how to answer those who aren’t named Develop amplification plans with partners and customers across social posts, blogs, newsletters, and their own announcements, and turn cohort results into joint customer and partner stories Grow the Academy’s presence on LinkedIn and other social channels with content that showcases programs, cohorts, and graduates Own the Academy’s web presence and any paid promotion, working with our web team and with creative and agency partners Build a community program that keeps cohort members and badge holders connected and turns them into advocates for the Academy Work with Brand to extend the Academy’s naming and brand architecture as new programs launch, keeping it consistent with, and clearly distinct from, Anthropic’s other education and training offerings Learn Anthropic’s other education and training programs, such as Claude Academy, Claude certifications, and Partner Basecamp, and work with their teams to define where Claude Frontier Academy fits, where the programs connect, and how they reference each other, so partners and customers see one clear path Equip Account Teams and Partner Account Managers with FAQs, internal announcements, and guidance so they can answer questions, help customers and partners register their interest, and set clear expectations on participation Keep senior stakeholders aligned through regular status updates and clear recommendations, and define and report on success metrics for Academy marketing Minimum qualifications Have built and run branded B2B marketing programs at a software/SaaS technology company, such as customer education, certification, community, or user conference programs Have marketed education, training, or certification programs at a technology company, such as a partner, customer, or developer academy Bring a creative, brand-minded approach and know how to create market moments that get noticed Have led major launches or announcements, coordinating press, social, and partner amplification, and keeping everyone aligned through legal review, executive edits, and date changes Know how to build an audience and spark conversation on LinkedIn and other social channels with B2B audiences Have strong executive presence and are comfortable giving updates and making recommendations to senior leaders Can operate at both strategic and tactical levels, comfortable owning an annual plan and rolling up your sleeves to ship Build trusted relationships with partners, customers, and cross-functional teams, and can drive approvals and commitments without formal authority Are an excellent writer who can move easily between press releases, FAQs, and social posts Are energized by ambiguity and by building something new as a first-in-seat marketer Passionate about AI diffusion and bringing the benefits of AI to people and the world Preferred qualifications 8+ years of B2B software marketing experience spanning brand, communications, or program marketing Experience building community or advocacy programs where members promote the program themselves Experience marketing to technical audiences, particularly engineers and developers Experience running joint announcements with global system integrators, consulting firms, or enterprise customers Experience marketing to enterprise technology leaders, such as CIOs and CTOs Experience marketing AI/ML products Role-specific policy: For this role, we expect all staff to be able to work from our San Francisco office at least 2 days a week, though we encourage you to apply even if you might need some flexibility for an interim period of time for relocation. Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $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: San Francisco WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW We’re looking for an experienced, hands-on Field Marketing Manager to own and execute our field marketing strategy. This role blends best-in-class tactical execution with strategic planning and operational rigor. You’ll lead the planning and delivery of first-party and third-party events, regional activations, and integrated campaigns designed to drive pipeline, lead generation, and revenue impact across the US market. This is an individual contributor role for a self-starter who thrives in a fast-paced, evolving environment and partners closely with GTM. You’ll be expected to build programs and processes from the ground up, continuously iterate and improve how we operate, and roll up your sleeves to execute—from developing the strategy and playbooks to being on the ground making it happen. WHAT YOU'LL DO - Own the planning and execution of US field marketing programs, including first-party events (executive dinners, roundtables, happy hours, and experiential events) and third-party events (conferences, sponsorships, partner activations). - Design and deliver field marketing initiatives that drive measurable pipeline and lead generation, aligned to regional targets, priority accounts, and GTM objectives. - Partner closely with the US GTM team to develop territory-based and account-focused event strategies, including pre- and post-event engagement and follow-up. - Manage end-to-end event delivery, including budgets, logistics, vendors, agencies, on-site execution, and post-event reporting. - Lead the development of scalable field marketing playbooks, processes, and best practices to support growth and consistency globally. - Own and manage relationships with external agencies, event partners, and third-party organizers, ensuring high-quality delivery and strong ROI. - Track, analyze, and report on the performance of field marketing activities, using data and insights to continuously improve impact and efficiency. WHAT YOU HAVE - 4–7 years of experience in field marketing, event marketing, or demand generation within B2B SaaS or professional services. - Proven ability to deliver high-impact field events and activations that drive measurable pipeline and lead generation. - Strong experience partnering with Sales on territory-based or account-focused marketing initiatives. - Excellent communication, organization, and stakeholder management skills, with a high bar for execution and detail. - Familiarity with tools such as Salesforce, Marketo (or similar), and event platforms is highly desirable. - Experience marketing to legal, financial services, consulting, or other high-touch professional audiences is a plus. COMPENSATION $ 120,000 - $160,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-LT1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: United States; Canada Workplace: OnSite WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! As a Senior Security Operations Engineer you will: - Serve as trusted advisor to team’s leadership and partner teams by clearly articulating business risks associated with security issues - Harden our cloud-native environments (AWS, OCI, GCP) by introducing secure by default cloud controls - Own and drive resolutions for enabling engineers to design, build, and use infrastructure securely at scale by paving the secure path using infrastructure-as-code modules and reusable code libraries - Manage IAM / RBAC for cloud infrastructure, and partner with IT on streamlining authentication/authorization to ensure unified access control across the board - Deploy, integrate and operationalize security platforms and services including but not limited to SIEM, SOAR, domain monitoring, endpoint tooling, cloud security tooling - Respond to security incidents and harden environments post-incidents. - Support control monitoring and remediation for compliance initiatives - Gather and analyze security metrics to address security issues with cross-team dependencies - Partner empathetically with engineering teams to understand their needs and deliver practical, scalable security solutions without creating unnecessary friction. You may be a good fit if: - 5+ years previous experience in SecOps, DevSecOps, Cloud Security, Threat Detection & Response or software development with a strong focus on security engineering. - You’re a hands-on security engineer interested in automating controls and building scalable solutions rather than relying on manual processes. - You have experience in managing cloud platforms (GCP, AWS, Azure, OCI) and Kubernetes environments - Familiarity with CI/CD systems and SecOps workflows (Git, Terraform) in cloud environments (GCP, AWS, Azure, OCI) - Have practical experience with one or more of : infrastructure automation, network segmentation, system hardening, container and cloud security concepts, and security observability - You have experience with multiple languages such as Golang and/or Python - Are comfortable navigating ambiguity, making informed decisions with incomplete information, and adapting your approach as requirements evolve. - You employ a flexible and constructive approach when solving problems - You are able to make trade-offs between build vs. buy decisions - help build solutions and able to review what tools are available - You understand secure engineering best practices, can articulate problem statements and propose solutions to both technically savvy and non-technical audiences FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: San Francisco Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack. We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Scale our post-training stack, supporting SFT and RL on leading open-weight models. - Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks. - Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation. - Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability. - Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result. - Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments. - Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely. - Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation. WHAT YOU HAVE - Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation. - Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks. - Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack. - Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus. - Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: Remote Workplace: Remote WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack. We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Scale our post-training stack, supporting SFT and RL on leading open-weight models. - Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks. - Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation. - Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability. - Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result. - Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments. - Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely. - Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation. WHAT YOU HAVE - Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation. - Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks. - Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack. - Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus. - Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: London Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack. We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Scale our post-training stack, supporting SFT and RL on leading open-weight models. - Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks. - Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation. - Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability. - Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result. - Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments. - Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely. - Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation. WHAT YOU HAVE - Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation. - Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks. - Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack. - Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus. - Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve. We are hiring for this role across multiple levels. DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: New York Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack. We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Scale our post-training stack, supporting SFT and RL on leading open-weight models. - Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks. - Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation. - Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability. - Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result. - Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments. - Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely. - Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation. WHAT YOU HAVE - Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation. - Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks. - Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack. - Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus. - Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: San Francisco Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work. We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows. - Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail. - Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows. - Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation. - Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination. - Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most. - Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions. WHAT YOU HAVE - Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code. - A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead. - The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria. - Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: London Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work. We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows. - Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail. - Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows. - Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation. - Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination. - Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most. - Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions. WHAT YOU HAVE - Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code. - A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead. - The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria. - Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work. We are hiring for this role across multiple levels. DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: Remote Workplace: Remote WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work. We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows. - Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail. - Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows. - Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation. - Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination. - Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most. - Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions. WHAT YOU HAVE - Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code. - A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead. - The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria. - Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: New York Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work. We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows. - Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail. - Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows. - Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation. - Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination. - Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most. - Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions. WHAT YOU HAVE - Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code. - A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead. - The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria. - Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai