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Location: United States Workplace: Remote Webflow is the agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize high-performing web experiences that drive predictable growth and strengthen brand trust. Building at Webflow will need grit, because we move fast, without ever sacrificing craft or quality. We’re looking for a Legal Counsel, Employment to help us support a growing global team the Webflow way: moving quickly, working collaboratively, and staying thoughtful about risk. You’re a bright, pragmatic, self-motivated employment attorney with 4+ years of counseling and litigation experience at a law firm and/or in-house. You’ll use that background to give timely, practical, business-minded advice, primarily to our Employee Relations and People teams around the world, so they can do their best work without unnecessary barriers. You have experience litigating and/or counseling on compliance with federal and state anti-discrimination, harassment, and retaliation laws, ideally including analysis under California law. Prior in-house or seconded experience at a technology company is a plus, but not required. You’re an entrepreneurial, resourceful self-starter who thrives in a fast-paced, dynamic environment, builds strong relationships, and is curious about supporting a global workforce. ABOUT THE ROLE: - Location: Remote-first (United States) - Full-time - Permanent - Exempt - The cash compensation for this role is tailored to align with the cost of labor in different geographic markets. We've structured the base pay ranges for this role into zones for our geographic markets, and the specific base pay within the range will be determined by the candidate’s geographic location, job-related experience, knowledge, qualifications, and skills. - United States (all figures cited below are in USD and pertain to workers in the United States) - Zone A: $158,000 - $190,000 - Zone B: $148,000 - $178,000 - Zone C: $140,000 - $168,000 This role is also eligible to participate in Webflow's company-wide bonus program. Target amounts are a percentage of base salary and vary by career level. Payouts are based on company performance against established financial and operational goals. Please visit our Careers page https://webflow.com/careers#pay-zones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter. - Application Information: - Application deadline: applications accepted on an ongoing basis until position is closed and filled - This posting is for an existing vacancy - Reporting to the Associate General Counsel, Corporate As Legal Counsel, Employment, you’ll: - Give practical, day-to-day employment advice on a wide range of issues, including HR practices, performance management, terminations, leaves of absence, investigations, and accommodations. Help the business move fast while staying clear-eyed about legal risk. - Investigate and manage pre-litigation and litigation matters. Build and carry out strategies for early resolution where it makes sense, and partner with outside counsel when needed. - Interpret and advise on policies and procedures using your knowledge of state, federal, and international employment laws (e.g., FMLA, ADA, FLSA, NLRA, Title VII, and their state and international equivalents). Turn them into guidance people can actually use. - Support a global workforce with legal counsel that works across borders, cultures, and time zones. - Partner closely with Webflow’s Employee Relations and People teams on employee complaints, investigations, performance management, and accommodations. - Collaborate with the Employment Legal and People teams to build strong, scalable processes that keep us compliant with applicable state, federal, and local laws. - Track developments in employment law across U.S. jurisdictions and internationally, and spot emerging trends early so Webflow can get ahead of them. ABOUT YOU: Requirements: - 4+ years of employment law experience at a leading law firm and/or in-house, with an interest in advice and counseling - Global workforce experience is a plus, not a requirement. If you’ve supported teams across borders in-house, you’ll have a head start with a company that works across time zones and jurisdictions. - Non-negotiable requirements - Active member in good standing of a State Bar, and eligible to practice in the jurisdiction where you’re based. - J.D. from a top-tier law school. You’ll thrive as Legal Counsel, Employment if you: - Are a sharp problem-solver with sound judgment and excellent written, verbal, and interpersonal communication. You can make complex legal topics clear and useful for the business. - Think creatively and strategically on your feet. You stay steady under pressure, juggle complex workloads and shifting priorities across many stakeholders, and help teams move quickly with confidence while staying thoughtful about risk. - Are a resourceful self-starter who is driven by results, finds a path where others see a barrier, and works with Webflow’s collaborative, innovative spirit. You hold yourself to high standards and strong ethics. - Build trust with cross-functional partners across the Legal Department and the company, and be the kind of counsel teams want to bring in early. - Stay curious and open to growth — demonstrating a proactive embrace of AI, and actively building and applying fluency in emerging technologies to elevate how we work, drive faster outcomes, and expand collective impact. OUR CORE BEHAVIORS - Build lasting customer trust. We build trust by taking action that puts customer trust first. - Win together. We play to win, and we win as one team. Success at Webflow isn't a solo act. - Reinvent ourselves. We don't just improve what exists, we imagine what's possible. - Own it all the way. We move fast because the moment demands it, and we hold ourselves accountable to deliver outcomes — for each other, and for customers.   BENEFITS - Ownership in what you help build. Every permanent Webflower receives equity (RSUs) in our growing, privately held company. - Health coverage that actually covers you. Comprehensive medical, dental, and vision plans for full-time employees and their dependents, with Webflow covering most premiums. - Support for every stage of family life. 12 weeks of paid parental leave for all parents and 6+ weeks of additional paid leave for birthing parents. Plus inclusive care for family planning, menopause, and midlife transitions. - Time off that’s actually off. Flexible vacation, paid holidays, and a sabbatical program to help you recharge and come back inspired. - Wellness for the whole you. Access to mental health resources, therapy and coaching. - Invest in your future. A 401(k) with 100% employer match (up to $6,000/year) in the U.S., and support for retirement savings globally. - Stipends to support our distributed team. Localized support for cell, Wi-Fi, and WFH expenses to help you settle into your best remote life. - Bonus for building together. All full-time, permanent, non-commission employees are eligible for our annual WIN bonus program.   Temporary employees may be eligible for paid holiday and time off, statutory leaves of absence, and company-sponsored medical benefits depending on their Fixed Term Contract and their country/state of employment.   BE YOU, WITH US At Webflow, equality is a core tenet of our culture. We are an Equal Opportunity (EEO)/Veterans/Disabled Employer and are committed https://webflow.com/diversity-equity-inclusion to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences. Employment decisions are made on the basis of job-related criteria without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by applicable law. Pursuant to the San Francisco Fair Chance Ordinance, Webflow will consider for employment qualified applicants with arrest and conviction records.   STAY CONNECTED Not ready to apply, but want to be part of the Webflow community? Consider following our story on our Webflow Blog https://webflow.com/blog, LinkedIn https://www.linkedin.com/company/webflow-inc-/, X (Twitter) https://twitter.com/webflow, and/or Glassdoor https://www.glassdoor.com/Reviews/Webflow-Reviews-E890506.htm.   PLEASE NOTE: We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Upon interview scheduling, instructions for accommodation requests will be administered. To join Webflow, you'll need a valid right to work authorization depending on the country of employment. If you are extended an offer, that offer may be contingent upon your successful completion of a background check, which will be conducted in accordance with applicable laws. We may obtain one or more background screening reports about you, solely for employment purposes. Webflow uses AI tools to assist in screening and evaluating applications. AI does not make final hiring decisions. For details on how we process your personal information, see Webflow’s Applicant Privacy Notice https://webflow.com/legal/applicant-privacy-notice.

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. Senior Director, Strategic Development Position Overview Sony Interactive Entertainment is entering an important new chapter in its evolution looking to expand business and identify future growth opportunities. This is a senior leadership position for an individual who combines exceptional strategic judgment with the ability to activate change across complex, highly accomplished organizations. The successful candidate will help SIE move beyond strategy as an annual planning exercise toward a continuous discipline of strategic choices, organizational alignment, experimentation, and measurable business outcomes. Working directly within the Business Strategy team alongside senior leaders across PlayStation, this individual will build the frameworks, decision mechanisms, and leadership practices that enable executives to own the outcomes of the company's strategic evolution. The central purpose of this role is not simply to develop strategy. It is to help the organization become better at continuously making, activating, and adapting strategic decisions. Key Responsibilities Activate PlayStation's Strategic Transformation Translate PlayStation's long-range strategic direction into clear, actionable enterprise priorities that connect the company's existing strengths with future growth opportunities. Help operationalize the strategic shifts defining PlayStation's evolution, including developing new value propositions, driving business model adaptation to new customers and opportunities and moving from periodic planning to continuous strategic adaptation. Establish practical frameworks that clarify what SIE must preserve, evolve, and newly develop over the next three to five years. Partner with functional executives to translate enterprise strategy into meaningful choices, commitments, and measurable outcomes within their organizations. Identify structural, cultural, and operational barriers to transformation and help leadership teams address them. Activate the strategy by embedding it within cross functional leaders to own it and adapt it as assumptions change. Establish Continuous Strategic Planning and Adaptation Build a strategy capability that operates throughout the year, responding to market shifts, emerging technologies, competitive developments, and organizational learning. Design and implement a continuous strategy operating rhythm, connecting three-to-five-year ambitions with annual priorities, quarterly strategic reviews, and ongoing opportunity assessment. Develop scenario-planning, strategic sensing, and portfolio-evaluation frameworks that allow leadership to anticipate change rather than simply respond to it. Connect insights from product, commercial, finance, technology, studios, and external partners into an evolving view of PlayStation's future. Create the right level of materials for decision-oriented executive forums and then orchestrate those important meetings to find emerging opportunities, challenge assumptions, and recommend adjustments to strategic priorities. Build mechanisms for leaders to revisit investment assumptions and reallocate attention and resources as evidence changes. Influence and Mobilize Cross-Functional Executive Leadership Serve as a trusted strategic partner to senior leaders, bringing together different perspectives and enabling collective decisions on issues that transcend individual business units. Build trusted relationships with VP- and SVP-level leaders across PlayStation and Sony Group. Facilitate high-stakes strategic conversations involving competing priorities, resource constraints, and differing perspectives on the future. Use rigorous analysis (both internal and external), commercial judgment, and compelling narratives to influence decisions without relying on formal authority. Help executive teams move from conceptual agreement to explicit decisions, accountable ownership, and coordinated action. Challenge established assumptions constructively while demonstrating respect for the achievements and operational realities of existing businesses. Identify and resolve strategic misalignment before it becomes an impediment to execution. Develop the Core / Explore Strategic Framework Support the development of two distinct but interconnected operating models that allow PlayStation to maximize current business performance while investing in future opportunities. Establish differentiated frameworks for evaluating core-business optimization and higher-uncertainty exploration initiatives. Help define how future opportunities are identified, validated, incubated, prioritized, and transitioned into scaled operating businesses. Partner with Finance and operating leaders to develop portfolio-level investment frameworks that balance near-term returns with longer-term strategic value. Create transparent decision criteria for advancing, redirecting, or discontinuing strategic initiatives. Ensure exploration activities are commercially grounded without subjecting early-stage opportunities to inappropriate mature-business performance expectations. Support leadership in determining where shared capabilities, resources, and partnerships can accelerate both operating systems. Strengthen Enterprise Strategy Execution and Organizational Capability Create repeatable approaches that allow SIE leaders to turn strategic direction into coordinated organizational progress. Develop executive-level strategy activation frameworks, including strategic outcome maps, decision rights, leadership commitments, and progress measures. Partner with team members to create processes for translating strategic choices into functional priorities without creating unnecessary reporting or bureaucracy. Facilitate leadership working sessions that resolve trade-offs and create durable ownership of agreed outcomes. Build strategy toolkits and practical methodologies that functional teams can adopt independently. Capture and institutionalize lessons from strategic initiatives, including successes, unsuccessful experiments, and changing market assumptions. Introduce AI-enabled research, synthesis, scenario modeling, and knowledge-management capabilities that increase the speed and quality of strategic work. Required Experience and Qualifications The ideal candidate will bring 15+ years of progressive experience in enterprise strategy, business transformation, corporate development, strategic operations, or product leadership, including substantial experience influencing senior executives within complex global organizations. A proven record of leading enterprise-wide strategic transformation, with tangible examples of changes adopted by business leaders and sustained beyond the initial initiative. Deep experience influencing cross-functional leadership teams, particularly in situations involving ambiguous authority, competing priorities, and significant organizational complexity. Demonstrated success designing and implementing strategic planning, portfolio management, or governance frameworks that improved actual business decisions. Experience in technology platforms, gaming, digital entertainment, consumer ecosystems, or similarly dynamic industries. Strong commercial and financial judgment, including the ability to evaluate investment trade-offs, growth opportunities, and long-range enterprise value. Exceptional executive communication, facilitation, and strategic storytelling capabilities. Experience navigating global organizations and multicultural leadership environments. Demonstrated ability to use emerging AI and analytical capabilities to improve strategic effectiveness. 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. The estimated base pay range for this role is listed below. $275,000 — $412,400 USD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

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

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 own 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 post-training recipe across SFT and RL, including reward design and verification for challenging, semi-verifiable legal tasks. You’ll help set the research direction and carry ideas from experiments through training runs to models used by customers. 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 and scientists who have gotten training runs working at scale, are immersed in RL for language models, and want their work to reach users quickly. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Own and pursue a research agenda to improve model capability on long-horizon legal reasoning and agentic workflows. - Design and run post-training experiments across SFT and RL, building on leading open-weight models. - Develop reward functions and verifiers for semi-verifiable tasks, including rubrics, learned preference models, and expert preference data, and study where they break. - Run and debug training at scale, addressing divergence, reward hacking, and instability. - Build and use rigorous evals to track improvements and decide what ships. - Design, implement, test, and debug code across our research stack. WHAT YOU HAVE - Hands-on experience post-training LLMs with SFT and RL, including preference optimization, and direct ownership of training runs and results. - Deep ML fundamentals and experience getting distributed training runs working reliably. - Strong engineering skills in Python, with production-quality code and end-to-end system ownership. - Research experience in RL for language models or reward modeling, with the ability to move quickly from experiments to shipped improvements. Publications welcome, not required. 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 own 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 post-training recipe across SFT and RL, including reward design and verification for challenging, semi-verifiable legal tasks. You’ll help set the research direction and carry ideas from experiments through training runs to models used by customers. 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 and scientists who have gotten training runs working at scale, are immersed in RL for language models, and want their work to reach users quickly. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Own and pursue a research agenda to improve model capability on long-horizon legal reasoning and agentic workflows. - Design and run post-training experiments across SFT and RL, building on leading open-weight models. - Develop reward functions and verifiers for semi-verifiable tasks, including rubrics, learned preference models, and expert preference data, and study where they break. - Run and debug training at scale, addressing divergence, reward hacking, and instability. - Build and use rigorous evals to track improvements and decide what ships. - Design, implement, test, and debug code across our research stack. WHAT YOU HAVE - Hands-on experience post-training LLMs with SFT and RL, including preference optimization, and direct ownership of training runs and results. - Deep ML fundamentals and experience getting distributed training runs working reliably. - Strong engineering skills in Python, with production-quality code and end-to-end system ownership. - Research experience in RL for language models or reward modeling, with the ability to move quickly from experiments to shipped improvements. Publications welcome, not required. 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 own 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 post-training recipe across SFT and RL, including reward design and verification for challenging, semi-verifiable legal tasks. You’ll help set the research direction and carry ideas from experiments through training runs to models used by customers. 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 and scientists who have gotten training runs working at scale, are immersed in RL for language models, and want their work to reach users quickly. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Own and pursue a research agenda to improve model capability on long-horizon legal reasoning and agentic workflows. - Design and run post-training experiments across SFT and RL, building on leading open-weight models. - Develop reward functions and verifiers for semi-verifiable tasks, including rubrics, learned preference models, and expert preference data, and study where they break. - Run and debug training at scale, addressing divergence, reward hacking, and instability. - Build and use rigorous evals to track improvements and decide what ships. - Design, implement, test, and debug code across our research stack. WHAT YOU HAVE - Hands-on experience post-training LLMs with SFT and RL, including preference optimization, and direct ownership of training runs and results. - Deep ML fundamentals and experience getting distributed training runs working reliably. - Strong engineering skills in Python, with production-quality code and end-to-end system ownership. - Research experience in RL for language models or reward modeling, with the ability to move quickly from experiments to shipped improvements. Publications welcome, not required. 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 own 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 post-training recipe across SFT and RL, including reward design and verification for challenging, semi-verifiable legal tasks. You’ll help set the research direction and carry ideas from experiments through training runs to models used by customers. 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 and scientists who have gotten training runs working at scale, are immersed in RL for language models, and want their work to reach users quickly. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Own and pursue a research agenda to improve model capability on long-horizon legal reasoning and agentic workflows. - Design and run post-training experiments across SFT and RL, building on leading open-weight models. - Develop reward functions and verifiers for semi-verifiable tasks, including rubrics, learned preference models, and expert preference data, and study where they break. - Run and debug training at scale, addressing divergence, reward hacking, and instability. - Build and use rigorous evals to track improvements and decide what ships. - Design, implement, test, and debug code across our research stack. WHAT YOU HAVE - Hands-on experience post-training LLMs with SFT and RL, including preference optimization, and direct ownership of training runs and results. - Deep ML fundamentals and experience getting distributed training runs working reliably. - Strong engineering skills in Python, with production-quality code and end-to-end system ownership. - Research experience in RL for language models or reward modeling, with the ability to move quickly from experiments to shipped improvements. Publications welcome, not required. 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, CA • New York, NY • United States Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! We’re looking for a strategic, entrepreneurial Product Manager to help shape the future of Collab Tools. Collab Tools includes FigJam, Figma Slides, and Figma Specs. You’ll be at the forefront of defining how product teams plan, capture intent, and communicate: from the initial brainstorm to the functional prototype. As we integrate AI to make these workflows more intuitive and powerful, you’ll help us build the next generation of surfaces that empower teams to align and execute faster than ever. What you’ll do at Figma: Own the strategy and roadmap for one of our key products (e.g. FigJam), and help drive our vision of Collab Tools as the defacto surfaces for upstream planning and discovery. Partner deeply with Design and Engineering to ship both foundational improvements and 0-to-1 bets, holding a high bar for craft and consumer-grade quality. Synthesize quantitative, qualitative, and market signals into a sharp point of view on what to build and why. Build durable relationships across your direct team, the broader pillar, and cross-functional partners, including the executive team. Define and run agent evals defined by our vision and grounded in real user behavior to measure and improve quality, latency, and cost. Push the frontier of AI-native product development in what you ship and in how the team plans and builds. Operate your area end-to-end, from long-term strategy through launch and iteration, moving fast without dropping standards. We’d love to hear from you if you have: 5-7+ years of product management experience, with a track record of shipping meaningful, well designed, consumer-grade products at B2B companies. Comfort with ambiguity and a demonstrated ability to develop and defend a clear point of view. Hands-on experience building and shipping agentic experiences, including defining evals, designing applied AI products, and navigating tradeoffs around quality, reliability, latency, and cost. Fluency with the latest AI tools and genuine curiosity and excitement about how EPD teams are changing because of them. A track record of moving fast, even inside a larger organization. Fluency across quantitative, qualitative, and market signals to fuel prioritization and decisions. Strong communication and organizational skills at every level, from IC to executive. While it’s not required, it’s an added plus if you also have: Previous experience in an engineering or design role, deeper technical chops, or interesting side projects. Experience at both a smaller company and a more mature, late-stage or public company. At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Pay Transparency Disclosure Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. Figma offers equity to employees, as well as a competitive package of additional benefits, including health, dental, and vision coverage; retirement benefits with company contributions; parental leave and reproductive or family planning support; mental health and wellness benefits; and paid time off. Figma provides paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws, including the requirements of the Washington Minimum Wage Act and related regulations. Exempt employees are eligible for employer‑provided paid flexible PTO in addition to flexible paid sick leave. PTO is subject to manager approval. Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts. Figma also offers sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles. All compensation and benefits are subject to applicable plan terms and may be modified by Figma at any time, consistent with applicable law. Annual Base Salary Range: $169,000 — $303,000 USD At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status , or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com . These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities. Examples of accommodations include but are not limited to: Holding interviews in an accessible location Enabling closed captioning on video conferencing Ensuring all written communication be compatible with screen readers Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice . Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles: Candidates may submit up to 5 applications during any rolling 30-day period. Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection. Once the applicable days has passed, candidates are welcome to apply again.

Location: Remote Workplace: Remote Hi, we’re Gravie. Our mission is to create health benefits that actually benefit small and midsize businesses and their employees. Our innovative benefit solutions and services are developed and delivered by a diverse group of unique people. We encourage you to be your authentic self - we like you that way. ABOUT THE ROLE We are seeking a Director of Corporate Compliance and Privacy to lead and mature our healthcare compliance and privacy programs. This leader will build and coach two managers, one for compliance and one for privacy, who each lead a team of junior-level professionals. The Director will partner closely with clinical, operational, technology, and business leaders and apply sound judgment in a complex, fast-changing regulatory environment. You will be a trusted advisor who helps the organization deliver care and grow responsibly while protecting health plan members, their data, the organization's integrity, and its reputation. KEY RESPONSIBILITIES PROGRAM LEADERSHIP: - Design, implement, and continuously improve the compliance program in line with the elements of an effective compliance program described in federal guidance (e.g., HHS-OIG), including policies, training, monitoring, auditing, and reporting - Assess emerging healthcare regulatory and privacy risks and translate them into practical, risk-based controls - Report regularly to executive leadership and the Board or Compliance Committee on program effectiveness, key risks, and trends PRIVACY PROGRAM LEADERSHIP: - Oversee the privacy program, including HIPAA Privacy Rule compliance, state health privacy and consumer data privacy laws, and privacy policies, notices, and training - Direct privacy incident and breach response in coordination with Security, Legal, and business owners, including risk assessments and required notifications - Oversee privacy reviews of new products, systems, vendors, and data uses, including privacy impact assessments and business associate agreements - Oversee the health plan member rights request program, ensuring timely, compliant handling of requests for access, amendment, accounting of disclosures, restrictions, and confidential communications, in accordance with HIPAA and applicable state law. - Serve as a point of contact for privacy regulators, and work with the Security Officer to align privacy and security controls TEAM LEADERSHIP: - Lead, develop, and hold accountable the Compliance Manager and the Privacy Manager, who each manage junior-level team members - Coach and mentor both managers to build their leadership capability, set clear goals, and develop strong succession pipelines - Set shared priorities and clear division of work between the compliance and privacy teams, and make sure they coordinate on overlapping issues - Plan for resourcing, structure, and long-term capability of the function, including a distributed and remote team CROSS-FUNCTIONAL PARTNERSHIP: - Build and maintain trusted relationships across the organization - Embed compliance and privacy considerations early into business processes and decisions as a collaborative partner rather than a gatekeeper - Influence stakeholders at all levels, including senior executives and clinical leaders, without relying solely on formal authority ENTERPRISE RISK MANAGEMENT: - Operate the Compliance and Privacy programs as distinct risk levers within the purview of the Chief Compliance Officer, working in close coordination with Enterprise Risk Management and Internal Audit, and with business leaders, to integrate compliance and privacy risks into the enterprise risk framework. - Identify and assess compliance and privacy risks and provide them to Enterprise Risk Management for inclusion in the enterprise risk register, coordinating with Internal Audit and business leaders to ensure risks are consistently rated, owned, and addressed. - Translate risk analysis into clear recommendations and risk-acceptance decisions for senior leadership JUDGMENT AND DECISION-MAKING: - Make timely, well-reasoned decisions in ambiguous situations, even when information is incomplete, and clearly communicate the rationale and trade-offs - Lead internal reviews and investigations, escalate significant matters appropriately, and drive remediation to closure MONITORING, AUDITING, AND REPORTING: - Own the enterprise risk-based compliance and privacy auditing and monitoring program, including annual work planning informed by the enterprise risk register, execution, and follow-up, in coordination with Enterprise Risk Management and Internal Audit to avoid duplication and preserve independence - Oversee hotline and case management, exclusion screening, and corrective action plan tracking through resolution - Report on all aspects of the Compliance and Privacy programs, including monitoring and audit results, investigations, incidents, and corrective actions - Establish service level agreements (SLAs) for key compliance and privacy processes and track performance against them - Develop metrics and dashboards that give leadership meaningful visibility into compliance and privacy health - Present program results and SLA performance to the Compliance Committee quarterly - Manage relationships with regulators, external counsel, and auditors as needed PROJECT AND PROGRAM MANAGEMENT: - Plan, prioritize, and deliver multiple concurrent compliance and privacy initiatives (e.g., policy overhauls, system implementations, audit remediation, regulatory readiness efforts) on time and within scope - Set clear milestones, ownership, and status reporting for cross-functional projects - Apply sound project management practices and tools to coordinate work across a distributed team QUALIFICATIONS - Bachelors degree in business or a related field - 10+ years of professional experience in healthcare compliance, privacy, legal, risk, audit, or a related field - 5+ years experience building, leading, and coaching teams, including leading managers who in turn lead junior-level staff - 5+ years of experience and proven ability to build and sustain cross-functional partnerships and influence senior stakeholders, including the ability to explain complex regulatory and privacy topics to non-experts - Project management experience, evidenced by experience leading and delivering on complex, cross-functional initiatives - Strong judgment and decisiveness, evidenced by a track record of sound calls under uncertainty and time pressure - Working knowledge of healthcare regulatory requirements including ERISA, the ACA, the Consolidated Appropriations Act (No Surprises Act, price transparency, MHPAEA), IRS and DOL requirements for HRAs, and state TPA licensing and insurance laws - Working knowledge of health privacy and security requirements, including HIPAA/HITECH as they apply to business associates, breach notification rules, and state privacy laws - Experience conducting investigations and performing root cause analysis PREFERRED - MBA, JD, or other advanced degree, or certification such as CHC, CHPC, CCEP, CIPP/US, CIPM, CFE, or PMP - Experience in healthcare or a comparable regulated environment - Experience leading both compliance and privacy functions, or integrating them under one leader - Experience scaling a compliance or privacy function in a growing or changing organization - Familiarity with compliance and privacy technology, analytics, and case management tools A LITTLE MORE ABOUT US: - We know healthcare. Our company was founded and is still led by industry veterans who have started and grown several market-leading companies in the space. - We have raised money from top tier investors who share the same long-term vision as we do of building an industry defining company that will endure over the long run. We are well capitalized. - Our clients love us. Customer satisfaction rates among employees using Gravie health plans consistently rank above 80% – nearly 40 points above the industry average. - Our culture is unique. We tend to be non-hierarchical, merit-driven, opinionated but kind people who thrive working in a high-performance, fast-paced environment. People at Gravie care deeply about making a positive impact in the lives of the people we serve. BENEFITS Our unique benefits program is the gravy, i.e., the special sauce that sets our compensation package apart. In addition to standard health and wellness benefits, Gravie’s package includes alternative medicine coverage, flexible PTO, up to 16 weeks paid parental leave, paid holidays, a 401k program, transportation perks, education reimbursement, and 2 days of paid paw-ternity leave. JOB APPLICANTS If you apply for employment with Gravie, personal information collected via our applicant tracking vendor is subject to our standalone California Job Applicant Notice at Collection, accessible directly within the application workflow and separate from this Policy.

Location: Remote (United States | Canada) Workplace: Remote 1Password is growing. We’ve surpassed $500M in ARR and we’re continuing to accelerate, earning a spot on the Forbes Cloud 100 for four years in a row and teaming up with iconic partners like Oracle Red Bull Racing. About 1Password At 1Password, we’re building the foundation for a safe, productive digital future. Our mission is to unleash employee productivity without compromising security by ensuring every identity is authentic, every application sign-in is secure, and every device is trusted. We innovated the market-leading enterprise password manager and pioneered Unified Access Management, a new cybersecurity category built for the way people and AI agents work today. As one of the most loved brands in cybersecurity, we take a human-centric approach in everything from product strategy to user experience. Over 180,000 businesses, from Fortune 100 leaders to the world’s most innovative AI companies, trust 1Password to help their teams securely adopt the SaaS and AI tools they need to do their best work. If you're excited about the opportunity to contribute to the digital safety of millions, to work alongside a team of curious, driven individuals, and to solve hard problems in a fast-paced, dynamic environment, then we want to hear from you. Come join us and help shape a safer, simpler digital future. As a Senior Implementation Consultant on the Customer Success team, you’ll lead technical deployments and customer enablement for 1Password’s product suite, partnering with Project Managers, Technical Account Managers, and Solutions Architects to deliver successful outcomes for commercial and enterprise customers. You’ll combine hands-on configuration, project management, customer training, and technical guidance to help organizations adopt secure, effective ways of working. Your work will help customers protect access to the tools and information they rely on every day, advancing 1Password’s mission to make life easier and safer for everyone. How we’re using AI today Across GTM, we’re transforming the way we work with AI. We expect every seller, CSM, and team member to become a power user, using it daily to work smarter and move faster. AI is already embedded in how we operate – from real-time coaching that sharpens how we sell and interact with customers, to surfacing insights that help us anticipate needs – creating more time for meaningful customer engagement. If you’re excited to reshape how you think, make decisions, and drive growth with AI, you’ll feel right at home here. This is a remote opportunity within Canada and the US. What we're looking for: - 5+ years of experience leading technical implementations from planning through launch, with experience in implementation consulting, solutions engineering, customer onboarding, with a proven track record of leading software deployments for large or complex organizations in a related Business-to-Business (B2B) Software as a Service (SaaS) environment. - Combine strong technical aptitude with project management experience, including managing timelines, coordinating stakeholders, tracking time, and monitoring utilization. - Configure solutions and answer complex customer questions independently, knowing when to involve the right internal partners. - Understand identity and security concepts such as identity providers (IdPs), Single Sign-On (SSO), System for Cross-domain Identity Management (SCIM), Active Directory, Mobile Device Management (MDM), and Zero Trust. - Communicate clearly with technical practitioners, senior stakeholders, and audiences with different levels of technical knowledge. - Design and deliver engaging virtual and in-person training for enterprise administrators, executives, and end users. - Use artificial intelligence (AI), automation, and workflow improvements thoughtfully to reduce repetitive work and create reusable solutions. What you can expect: - Lead the hands-on configuration, integration, validation, and launch of 1Password’s Enterprise Password Manager, SaaS Manager, Device Trust, and Unified Access. - Partner with Project Managers on implementation plans, customer coordination, timelines, and delivery risks. - Collaborate with Technical Account Managers, Solutions Architects, and Customer Success partners to understand customer environments and align technical approaches with business goals. - Manage a portfolio of active customer engagements, balancing independently led implementations with training and enablement support for Project Manager-led projects. - Deliver customized technical consultations and training sessions, including occasional onsite sessions for customers. - Translate technical concepts into clear business value and help customers adopt solutions that support their security and operational goals. - Identify risks early, drive issues to resolution, and improve playbooks, training materials, processes, and AI-powered workflows that strengthen the customer experience. - Share implementation expertise with teammates through mentoring, knowledge sharing, and continuous improvement initiatives. - Travel occasionally for customer engagements, team events, or other business needs. USA-based roles only: The annual base salary for this role is between $102,000 USD and $148,000 USD, and is commission-eligible. This role is also eligible for immediate participation in 1Password's benefits program (health, dental, 401k and many others), utilization of our generous paid time off, an equity grant and, where applicable, participation in our incentive programs. Canada-based roles only: The annual base salary for this role is between $102,000 CAD and $148,000 CAD and is commission-eligible. This role is also eligible for immediate participation in 1Password’s generous benefits program (health, dental, RRSP and many others), utilization of our generous paid time off, an equity grant and, where applicable, participation in our incentive programs. At 1Password, we approach each individual's compensation with a promise of fair market value and internal equity commensurate with experience and specific skill set. This posting is for an existing vacancy. Our culture At 1Password, we prioritize collaboration, clear and transparent communication, receptiveness to feedback, and alignment with our core values: keep it simple, lead with honesty, and put people first. You’ll be part of a team that challenges the status quo, and is excited to experiment and iterate in search of the best solution. That said, 1Password is not for everyone https://blog.1password.com/inside-the-culture-powering-1passwords-next-chapter/. Our work is demanding, we strive for excellence, and the pace is fast. We need people who are keen to take on challenging problems, who seek feedback to grow, and who are driven to make an impact. If you're looking for a place where you can settle into a comfortable routine, this might not be the right fit for you. We’re looking for individuals who are proven experts in their fields, as well as those who are highly adaptable, can thrive in ambiguity and through change, are curious, and above all deliver results. How we work with AI We are committed to leveraging cutting-edge technology—including AI—to achieve our mission. We also understand that thinking critically about AI in its current forms will help us create better solutions for our customers and ourselves with its future forms, which will help us continue to close the gap between security and privacy and achieve our mission. We want team members at all levels to take the approach of actively learning AI best practices, identifying opportunities to apply AI in meaningful ways, and driving innovative solutions in their daily work. Embracing the future of AI isn't just encouraged—it's an essential part of how we will be successful at 1Password. This approach extends to our hiring process—candidates are welcome to use AI tools responsibly and thoughtfully during the application process. To us, this means we do ask that you join live interviews without using AI tools so we can get to know how you communicate, solve problems, and collaborate with others. Our approach to work We recognize the power of both in person collaboration and remote work. Some roles are designated as remote-first, with an expectation that individuals work from their homes majority of the time, while others are designated as in-office roles, with an expectation of being on-site on a regular basis. We recognize that certain roles benefit from regular, in-person connection to support collaboration, team cohesion, and customer engagement. For all roles, occasional travel may be required. This includes things like: department-wide offsites, quarterly department meetings and periodic customer events. These events are typically held in varying locations across Canada, USA and/or EMEA. In leadership roles, you can expect to travel once per month on average. Note: All go-to market roles will have an in-person onboarding in Toronto. What we offer We believe in working hard, and rewarding that hard work through our benefits. While not an exhaustive list, here is a glance at what we currently offer: Health and wellbeing 👶 Maternity and parental leave top-up programs 🩺 Competitive health benefits 🏝 Generous PTO policy Growth and future 📈 RSU program for most employees 💸 Retirement matching program 🔑 Free 1Password account Community 🤝 Paid volunteer days 🏆 Peer-to-peer recognition through Bonusly 🌎 Remote-first work environment *Some roles in our GTM team are currently being hired for in-person hybrid work in Toronto and Austin. These roles will specify on the posting. You belong here. 1Password is proud to be an equal opportunity employer. We are committed to fostering an inclusive, diverse and equitable workplace that is built on trust, support and respect. We welcome all individuals and do not discriminate on the basis of gender identity and expression, race, ethnicity, disability, sexual orientation, colour, religion, creed, gender, national origin, age, marital status, pregnancy, sex, citizenship, education, languages spoken or veteran status. Be yourself, find your people and share the things you love. Accommodation is available upon request at any point during our recruitment process. If you require an accommodation, please speak to your talent acquisition partner or email us at nextbit@agilebits.com and we’ll work to meet your needs. Remote work is a part of our DNA. Given that our company was founded remotely in 2005, we can safely say we're experts at building remote culture. That said, remote work at 1Password does mean working from your home country. If you've got questions or concerns about this, your talent partner would be happy to address them with you. Successful applicants will be required to complete a background check that may consist of prior employment verification, reference checks, education confirmation, criminal background, publicly available social media, credit history, or other information, as permitted by local law. 1Password uses artificial intelligence (AI) and machine learning (ML) technologies, including natural language processing and predictive analytics, to assist in the initial screening of employment applications and improve our recruitment process. See here https://www.ashbyhq.com/downloadables/ashby-bias-audit-08-2024.pdf for the latest third party bias audit information. If you prefer not to have your application assessed using AI/ML features, you may opt out by completing this form https://jobs.ashbyhq.com/1password/automation-notice. For additional information see our Candidate Privacy Notice https://1password.com/files/candidate-privacy-notice.pdf.

Location: Warsaw, Mazowieckie, Poland Workplace: hybrid We are a leading trading platform that is ambitiously expanding to the four corners of the globe. Our top-rated products have won prestigious industry awards for their cutting-edge technology and seamless client experience. We deliver only the best, so we are always in search of the best people to join our ever-growing talented team. We are looking for a Marketing Analyst to join our Marketing Intelligence & Automation team in Warsaw. Our marketing team already uses an AI-powered decision system to recommend where budget should go. What limits it today is measurement: the sharper our attribution, marketing mix models and experiments, the more decisions we can trust it to make. Your job is to strengthen that foundation and turn marketing data into insights that change how we invest. Responsibilities: Build, maintain and improve attribution models, and support new attribution model releases. Develop and refine marketing mix models (MMM) to understand channel contribution and guide budget allocation. Design and analyze incrementality tests and experiments to measure the true impact of marketing activity. Deliver regular reporting and deep-dive analysis on channel, campaign and user performance across markets. Turn findings into clear, actionable recommendations for marketing stakeholders, linked to acquisition cost, client value and revenue. Define and document marketing metrics and KPIs so the team works from one source of truth. Improve the measurement inputs that feed our AI-driven budget recommendation and automation systems. Partner with MarTech, analytics engineering and, increasingly, Product Marketing and CRM teams on shared measurement needs. Requirements: 3–5 years of experience in marketing analytics, growth analytics or a similar role. Experience in financial services, such as trading, brokerage, fintech or banking is a must . Hands-on experience with attribution modeling and/or marketing mix modeling. Strong SQL skills and experience working with large marketing datasets. Solid understanding of statistics and experimentation, including incrementality testing. Strong critical thinking: you structure ambiguous problems, challenge assumptions and connect analysis to business impact. Ability to explain complex findings clearly to non-technical stakeholders. Nice to have: Python (or R) for analysis and modeling. Hands-on experience with Tableau (or a similar BI tool) and analytics platforms like Google Analytics 4. Experience using AI tools or LLMs for analysis or workflow automation, at work or in your own projects. What you will get in return: Competitive Salary : We believe great work deserves great pay! Your skills and talents will be rewarded with a salary that makes you feel valued and motivated. Work-Life Harmony : Join a company that genuinely cares about you - because your life outside of work matters just as much as your time on the clock. #LI-Hybrid Annual Performance Bonus : Your hard work doesn’t go unnoticed! Celebrate your achievements with a well-deserved annual bonus tied to your performance. Generous Time Off : Need a breather? Our annual leave policy lets you recharge and enjoy life outside of work without a worry. Employee Referral Program : Love working here? Share the love! Bring your talented friends on board and get rewarded for growing our awesome team. Comprehensive Health & Pension Benefits : From medical insurance to pension plans, we’ve got your back. Plus, location-specific benefits and perks! Workation Wonderland : Live your digital nomad dreams with 30 extra days to work remotely from anywhere in the world (some restrictions apply). Adventure awaits! Volunteer Days : Make a difference! Take two additional paid days each year to support causes you care about and give back to the community.