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Location: 2405 Satellite Boulevard Suite 200, Duluth, GA 30096 Come join our team! There are many reasons why EPIC Insurance Brokers & Consultants has become one of the fastest-growing firms in the insurance industry. Fueled and driven by capable, committed people who share common beliefs and values and “bring it” every day, EPIC is always looking for people who have “the right stuff” – people who know what they want and aren’t afraid to make it happen. Headquartered in San Francisco and founded in 2007, our company has over 3,000 employees nationwide. With locations spread out across the U.S., our local market knowledge and industry expertise helps support our clients' regional and global needs. We have grown very quickly since our founding, and we continue to see growth and success thanks to our hard-working and growth-minded employees. Our core values are: Owner mindset, Inspire trust, Think big, and Drive results. If these values and growth align with what you're looking for in your next career? Then consider joining our amazing team! LOCATION: Duluth, Georgia, hybrid role- 3 days a week in the office. JOB OVERVIEW: The Account Manager serves as the primary day-to-day contact for employee benefits clients, delivering exceptional service and support throughout the client lifecycle. This role partners closely with Client Executives, carriers, internal departments, and clients to ensure a seamless experience while helping clients navigate benefits administration, compliance, enrollment, billing, and employee benefits programs. What You'll Do: Client Service & Account Management Serve as the primary day-to-day contact for assigned clients and build strong, trusted relationships. Partner with clients, Client Executives, and internal teams to execute comprehensive service plans. Coordinate and support open enrollment meetings, including preparation of employee communication materials. Complete COBRA paperwork for new group implementations and renewals. Maintain ongoing client communication regarding benefit trends, legislative changes, and regulatory updates. Collaborate with compliance specialists and Client Executives to support government reporting requirements and compliance initiatives. Maintain accurate client and benefits plan information within EPIC's CRM system. Resolve enrollment, eligibility, and basic claims issues while coordinating escalated claims with the claims department. Research and resolve billing discrepancies and administrative concerns. Keep Client Executives informed of client issues, concerns, and significant events. Participate in mentorship, training, and professional development activities. Operational Excellence Work closely with Client Executives to prioritize activities and manage workflows effectively. Maintain client documentation, activity logs, and agency management system records. Communicate professionally and collaborate effectively with colleagues, clients, and carrier partners. Stay current on industry developments, market trends, product offerings, legislation, and technology advancements. Consistently project a professional and customer-focused image. What You'll Bring Working knowledge of employee benefits programs, including: Fully insured plans Self-funded plans Level-funded plans Strong proficiency with Microsoft Office applications, including Outlook, Word, Excel, and PowerPoint. Excellent organizational skills with exceptional attention to detail. Strong time management and ability to manage multiple priorities in a fast-paced environment. Ability to work independently and collaboratively within a team setting. Effective written and verbal communication skills. Experience using agency management systems, HR portals, and related technology platforms. High school diploma required; some college coursework preferred. Minimum of 2 years of employee benefits account management experience with a brokerage, consulting firm, insurance carrier, TPA, or related organization. Demonstrated ability to manage competing deadlines while maintaining a high level of service. Strong professionalism, discretion, diplomacy, and ability to handle confidential information. Licenses & Certifications Georgia or Indiana Life & Health License, or ability to obtain within 60 days of hire. Valid driver's license. COMPENSATION: The base pay offered will be determined based on your experience, skills, training, certifications and education, while also considering internal equity and market data. WHY EPIC: EPIC has over 60 offices and 3,000 employees nationwide – and we’re growing! It’s a great time to join the team and be a part of this growth. We offer: Generous Paid Time off Managed PTO for salaried/exempt employees (personal time off without accruals or caps); 22 PTO days starting out for hourly/non-exempt employees; 12 company-observed paid holidays; 4 early-close days Generous leave time options: Paid parental leave, pregnancy disability and bonding leave, and organ donor/bone marrow donor leave Generous employee referral bonus program of $1,500 per hired referral Employee recognition programs for demonstrating EPIC’s values plus additional employee recognition awards and programs (and trips!) Employee Resource Groups: Women’s Coalition, EPIC Veterans Group Professional growth & development: Mentorship Program, Tuition Reimbursement Program, Leadership Development Unique benefits such as Pet Insurance, Cancer Insurance, Identity Theft & Fraud Protection Coverage, Legal Planning, Family Planning, and Menopause & Midlife Support Additional benefits include (but are not limited to): 401(k) matching, medical insurance, dental insurance, vision insurance, and wellness & employee assistance programs 50/50 Work Culture: EPIC fosters a 50/50 culture between producers and the rest of the business, supporting collaboration, teamwork, and an inclusive work environment. It takes both production and service to be EPIC! EPIC Gives Back – Some of our charitable efforts include Donation Connection, Employee Assistance Fund, and People First Foundation We’re in the top 10 of property/casualty agencies according to “Insurance Journal” To learn more about EPIC, visit our Careers Page: https://www.epicbrokers.com/about/epic-careers/ . EPIC embraces diversity in all its various forms—whether it be diversity of thought, background, race, religion, gender, skills or experience. We are committed to fostering a work community where every colleague feels welcomed, valued, respected and heard. It is our belief that diversity drives innovation and that creating an environment where every employee feels included and empowered, helps us to deliver the best outcome to our clients. California Applicants - View your privacy rights at: https://www.epicbrokers.com/wp-content/uploads/2025/01/epic-ca-employee-privacy-notice.pdf . #LI-SG1 #Hybrid

Location: New York Who We Are: Galaxy Digital Inc. (Nasdaq: GLXY) is a global leader in digital assets and data center infrastructure, growing the economy that runs on code. Galaxy delivers the onchain infrastructure that connects institutions to digital assets, including trading, advisory, asset management, staking, self-custody, and tokenization. Galaxy also develops and operates data center infrastructure to power AI and HPC workloads. Anchored by its Helios campus in Texas, Galaxy is building a multi-gigawatt pipeline of more than 5.7 GW of potential capacity, positioning it among the largest and fastest-growing data center developers in North America. The Company is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia. Additional information about Galaxy's businesses and products is available on www.galaxy.com . What We Value: We are a diverse team of free thinkers, and fast movers united to help investors and creators energize the global economy. We are looking for individuals who thrive in a culture of builders and overachievers and embrace high performance, transparent feedback, and a mission-first approach. Our culture shapes our way of working and gets us where we want to be. Seek Excellence. Be Selective To Be Effective. Be Highly Aligned, Loosely Coupled. Disagree Transparently. Encourage Independent Decision-Making. Build Dream Teams. About the Galaxy Summer Internship Program The Galaxy NYC Summer Internship Program is an immersive, nine-week experience taking place on-site in our New York HQ office. During the nine weeks, you will gain hands-on, practical work experience on our Investment Banking, working on real products and problems alongside the people building them. Interns join a lean team advising crypto and fintech companies on M&A, capital raising, and corporate strategy. In addition to learning on the job, Galaxy interns participate in professional development programming, social events, and networking opportunities with senior leaders. Program Dates : June 7th – August 6th, 2027 What You'll Do: Build and review financial analyses and valuation models, including comparable companies, precedent transactions, DCF, and merger models. Research companies and protocols using public filings, earnings calls, industry research, and onchain data. Map buyer and investor universes, analyze competitive landscapes, and assess business models and value drivers. Prepare pitch materials, management presentations, teasers, and internal committee memos. Support live deals through preparation, data room maintenance, and process tracking. Use AI tools to accelerate research and analysis, improve internal processes, and help develop AI-enabled workflows and agents. What We're Looking For: A genuine interest in crypto and investment banking, demonstrated through independent research, coursework, projects, or relevant experience. Initiative, intellectual curiosity, and sound judgement, with the ability to work through unfamiliar problems and ask thoughtful questions. Strong analytical skills and a foundational understanding of accounting, corporate finance, and valuation. Familiarity with blockchain technology, token economics, and how value accrues to companies, protocols, and tokens. Strong attention to detail, a collaborative approach, and the ability to manage competing deadlines. Clear, concise written and verbal communication, and the ability to simplify complex ideas. Bonus Points: Previous internship or work experience in crypto or investment banking. Financial or valuation models for companies, tokens, or protocols. Experience using AI tools beyond chat interfaces, including APIs, agents, or automated research and analysis workflows. Published writing, research or other work demonstrating original thinking about crypto businesses, protocols, or markets. Programming or data analysis experience (Python, SQL). Eligibility Requirements: Currently enrolled in an undergraduate degree program, with an expected graduation date between December 2027 and June 2028. Available to work on-site in New York City five days a week for the full program, June 7 – August 6, 2027. Students enrolled in PhD or JD programs are not eligible to apply. Here are some of the industry-leading benefits of interning at Galaxy: Opportunities to learn about the Digital Asset and Data Center industry Free daily snacks and weekly lunches Smart, entrepreneurial and fun colleagues Employee Resource Groups *Benefits may vary based on location. Interns are classified as non-exempt employees and will be paid a rate of $55/hr. Galaxy respects diversity and seeks to provide equal employment opportunities to all employees and job applicants for employment without regard to actual or perceived age, race, color, creed, religion, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression (including transgender status), sexual orientation, marital or partnership or caregiver status, ancestry, national origin, citizenship status, disability, military or veteran status, protected medical condition as defined by applicable state or local law, genetic information or predisposing genetic characteristic, or other characteristic protected by applicable federal, state, or local laws and ordinances. We will endeavor to make a reasonable accommodation to the known limitations of a qualified applicant with a disability unless the accommodation would impose an undue hardship on the operation of our business. If you believe you require such assistance to complete the application process or to participate in an interview, please contact careers@galaxy.com.

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

Location: New York Workplace: Hybrid Company Description We’re http://checkout.comCheckout.com http://Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started. Position Overview Checkout.com is one of the most exciting fintechs in the world. Our mission is to enable businesses and their communities to thrive in the digital economy. We’re the strategic payments partner for some of the best-known fast-moving brands globally such as Wise, Hut Group, Sony Electronics, Homebase, Henkel, Tamara and many others. Purpose-built with performance and scalability in mind, our flexible cloud-based payments platform helps global enterprises launch new products and create experiences customers love. And it's not just what we build that makes us different. It's how. We empower passionate problem-solvers to collaborate, innovate and do their best work. That’s why we’re on the Forbes Cloud 100 list and a Great Place to Work accredited company. And we’re just getting started. We’re building diverse and inclusive teams around the world — because that’s how we create even better experiences for our merchants and our partners. And we need your help. Join us to build the digital economy of tomorrow. The Revenue Enablement Specialist is responsible for supporting the wider Revenue Enablement team with content production, process management and improvements, reporting and communication. What you’ll do - Coordinate day-to-day delivery of our North America new-hire onboarding program using established plans and materials. Keep session schedules, logistics, learner communications, and follow-ups organized. - Facilitate engaging live sessions for new hires across Business Development, Sales, Account Management, and other customer-facing teams. - Create a supportive learner experience by adapting your facilitation to each cohort’s needs and experience. Share recommendations for content or program changes with the program lead. - Track attendance, completion, learner feedback, and other agreed program measures. Organize the data and summarize findings to help identify gaps and opportunities to improve. - Maintain accurate, easy-to-find learning resources in our learning and content platforms, and help colleagues follow good platform practices. - Support learning activities at flagship events such as Kick-Off, President’s Club, and Commercial Leadership Summits, coordinating logistics and learning needs with event owners. - Coordinate with partners across Commercial, People, Product, Operations, and Marketing to gather input and keep onboarding activities on track. WHAT YOU’LL BRING - 2-3 years of relevant experience; experience in FinTech, financial services, technology, or SaaS - Strong written and verbal communication, with confidence facilitating groups or a willingness to develop that skill. - Some experience supporting or delivering onboarding, training, learning programs, events, or enablement ideally for sales, customer success, or other customer-facing teams. - Good organization, attention to detail, and follow-through across multiple tasks and deadlines. - A collaborative, adaptable approach, including the ability to prioritize, ask for guidance, and work effectively as plans evolve. - Comfort working with feedback and basic program data to identify patterns and suggest improvements. - Interest in how commercial teams work and how learning can help them succeed. - AI native, Tech-savvy and data-driven HELPFUL, BUT NOT REQUIRED - Familiarity with a learning management system (LMS), content management system (CMS), or enablement platform. - Exposure to sales playbooks or methodologies such as Command of the Message, MEDDPICC, or an equivalent approach. - Familiarity with commercial or revenue cycles.   Additional Information Bring all of you to work We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands. We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here. It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. Life at Checkout.com http://Checkout.com We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. Curious about what it’s like to be part of our team? Visit our Careers Page https://www.checkout.com/careers to learn more about our culture, open roles, and what drives us. For a closer look at daily life at Checkout.com http://Checkout.com, follow us on LinkedIn https://www.linkedin.com/company/checkout/life/ and Instagram https://www.instagram.com/checkout_com/

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: Newstead, Australia; Brisbane, Australia About VALD VALD is the world leader in technology for the allied health industry, providing innovative human-measurement technology to over 13,000 clients in over 150 countries. If you have a favourite team in the NBA, EPL, or NFL, there’s a good chance they use VALD Technologies. Since its humble beginnings in 2015 in Brisbane, Australia, VALD has grown to a team of over 400 people in over 35 countries, with five offices across four continents. Driven by a multidisciplinary team of researchers, clinicians, sports scientists, designers, developers and engineers, VALD’s suite of systems offers unparalleled insight into human movement, performance, injury risk and rehabilitation. About the role You will be the engine room of VALD’s people related operations. You will make sure every new team member, wherever they are in the world, is contracted, set up and welcomed from day one. As the engine room of the employee lifecycle, you will also ensure that day to day processes and offboarding run smoothly. You will help shape the systems that will support VALD’s growth. As the function grows, so can your role and your career. This is a full-time, permanent role, based on-site in our Newstead office in Brisbane. You will be one of the first people new team members meet, and much of the work building those relationships happens face to face. As it stands, the role is hands-on, with a large part of your day spent on administrative processes. That is also the opportunity. You will help develop the processes. You will help introduce automation and employee self-service where they make things easier, but always keeping that personal touch that makes people feel welcome and seen. What you will do Process contract requests (including updates) for new team members across Australia, the US, Canada, the UK and our international contractor network. Administer background checks, and work with immigration advisors on visa and immigration requirements. Organise onboarding schedules and travel for new starters. Liaise with IT, Payroll and other teams so every new team member is set up in accordance with standard processes from day one. Manage offboarding, including exit documentation, systems access removal and final pay coordination with Payroll. Maintain employee records, people-related reports and registers across VALD’s systems. Act as a first point of contact for employment-related enquiries from team members. Support hiring managers with job ads, interview scheduling and candidate administration in Breezy Document and continuously improve people processes, identifying opportunities for automation and self-service. About you At least 2 years of experience in an HR administration, people operations or similar role. A tertiary qualification in HR, business or a related field (or working towards one) is desirable. High levels of attention to detail. Discretion with confidential information. Self-motivated and positive, and happier jumping in to help than waiting for another team member to pick something up. Warm and approachable, and enjoy making new people feel welcome. Satisfied by quiet, behind the scenes work that sets others up to succeed. Experience with HR information systems (HRIS), payroll or applicant tracking systems (ATS) (e.g. Employment Hero, Deel, ADP, Breezy) is an advantage. Experience in a fast-growing technology company or onboarding international hires will be highly regarded. What success looks like In the first twelve months, success looks like: Every new starter, in every country, is contracted, checked and fully set up for their first day. New starters arrive knowing where to be, who they'll meet and what their first week looks like, with travel sorted where needed. Contracts, contract variations and offboarding are processed accurately and on time, with minimal rework. Background checks and visa matters are resolved before they affect start dates. Employee records, reports and registers are accurate and can be relied on. Team members get timely, accurate answers to their enquiries. People processes are documented and improved, with automation and self-service introduced where they help, so the function is ready to scale. Business leaders see you as a reliable partner in recruitment and onboarding. Why VALD? VALD’s office is a great place to be, and we have exciting benefits and perks! We value our team, and this is just a taste of what we offer: Food: On-site chefs who prepare fresh breakfast and lunch, Monday to Friday. Coffee and Drinks: On-site barista to make your coffee just as you like it. Games: Table tennis and basketball court if that’s your thing. Health and Fitness: Access to the VALD gym, remedial sports massage therapy, and subsidised physiotherapy services. End-of-Commute Facilities: Showers, lockers, bike and scooter racks. Central Location: Based in Newstead, close to public transport. Strong Culture: A culture filled with a friendly, social, high-performing team. Diversity and inclusion commitment We’re committed to growing and empowering an inclusive VALD team. That’s why we actively encourage applications from candidates from all backgrounds, experiences, and perspectives. If you require accessibility assistance at any stage of the process, please let us know. Conditions of employment The successful applicant will be subject to a background check (including identity and criminal record checks). It will be a condition of employment that the background checks return acceptable results for the role.

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