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Location: Remote - US Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Principal Manager, Procurement Enablement & Contingent Workforce About the job Twilio is growing rapidly and seeking a Principal Manager, Procurement Enablement & Contingent Workforce to drive Procurement and contingent workforce process transformation. This high visibility role will transform our processes from manual entries to simplified agentic enabled processes. This role will take a long term vision to ensure we’re building our next generation of scalable processes as Twilio’s growth accelerates. Additionally, this role will be responsible for Procurement related systems, Procurement Compliance, and driving cross functional collaboration between multiple S2P teams. Responsibilities In this role, you’ll: Lead a team of 4 Procurement Enablement and Contingent Workforce (ITV) program managers who will work on Procurement and Contingent Workforce process governance, support, enablement, process improvement, and redesign. Manage all Procurement related systems and enhancements including Oracle P2P, Ironclad CLM, Pursuit RFP, Airtable Savings Tracker, and AI tools. Deliver on Procurement intake transformation including Agentic Intake Orchestration by designing and deploying next-generation, AI-driven conversational and autonomous agentic intake systems that replaces static forms. Drive Agentic in-take process to be fully comprehensive through multiple system integrations with ability to provide a guided buying experience, provide real time status updates, and provide renewal notifications and actions to both sourcing and business owners. Redesign the end to end Contingent Workforce process to provide hiring managers a simpler and faster hiring journey for Contingent Workers that reduces hand offs between the Procurement and Contingent Workforce program team. Oversee the Contingent Workforce program and governance including managing the VMS and its global expansion. Develop the global Contingent Workforce supply chain through identifying and driving a cohesive supply chain strategy and enabling hiring managers to find Contingent Workforce talent globally. Lead other S2P process enhancements and be the glue that drives cross functional collaboration between AP, Accounting, Security, Privacy, Audit, IT, and other functions. Responsible for driving Procurement Policy simplifications and enhancements. Lead cross functional training and enablement for hiring managers globally and also for all Procurement stakeholders. Track and manage preferred supplier list; identify then partner with sourcing on areas to increase preferred supplier usage. Lead development of an external supplier landing page that highlights supplier FAQ, how to navigate supplier portal, an invoice lookup tool, Twilio code of conduct, Sustainability expectations etc. Partner with Twilio sustainability team to lead on reporting of supplier GHG emissions. Drive simplification of our POC and NDA processes into a centralized agentic workflow. Partner with Procurement Legal to ensure contracting requirements and proper positioning of paper are built into any new or redesigned process — including agentic intake, guided buying, and POC/NDA workflows — so process speed doesn’t come at the cost of downstream legal or compliance rework. Partner with the Procurement Operations and Compliance team to implement an automated KYS screening for both vendors and carriers globally. Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! *Required: 12+ years of experience of managing procurement systems, S2P processes, and ITV/contingent workforce programs. Familiarity or participation in an ERP redesign with advance knowledge of Oracle Cloud Procurement. Strong understanding or experience in implementing Procurement agentic solutions that result in simpler and leaner processes. Familiarity or participation in an Contingent Workforce redesign with knowledge of Beeline or other VMS systems. Track record of successful cross-functional leadership, collaboration, and relationship building. Knowledgeable in requirements gathering, analysis, design and implementation methodologies Pragmatic and collaborative, able to work independently to ensure execution and on time delivery of programs to achieve objectives in procurement efficiency taking into consideration upstream/downstream partner processes, systems, security standards and compliance requirements. Solid understanding of contracting fundamentals and how contracting fits within the S2P process, with the ability to design or redesign intake, policy, and workflow changes that preserve proper contracting positioning rather than treating it as an afterthought. Tech savvy change agent who understands procurement and finance vendor landscape, tool capabilities/gaps and possible solutions. Knowledge of Netsuite, Coupa, or Oracle Cloud is strongly advantageous. Strong ability to manage multiple projects concurrently with sound business acumen. Excellent communication skills, able to communicate clearly and succinctly in writing, presentations and verbally to multiple levels within the organization. Strong project management skills (certifications a plus), the ability to track and manage complex processes, and a desire to lead teams and projects Bachelor's Degree or equivalent experience Desired: Experience in the Technology industry and operating within hyper-growth environments, with a proven ability to build scalable sourcing processes and systems from the ground up. Proven track record of cultivating collaborative, high-trust partnerships across matrixed internal business units and external vendor ecosystems to drive shared strategic outcomes. Demonstrated experience scaling, structuring, and developing a ITV/Contingent Workforce and procurement Process, and developing process change with Agentic workflows. Lean Six Sigma or similar process improvement experience. Location This role will be remote, but is not eligible to be hired in CA, CT, NJ, NY, PA, WA. Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, approximately <10%> travel is anticipated to help you connect in-person in a meaningful way. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Compensation *Please note the salary range information provided applies only to candidates residing in California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State due to local requirements. Compensation for candidates in other locations will be discussed during the hiring process. Please note that hiring for this role is not restricted to the locations listed above. The estimated pay ranges for this role are as follows: Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $141,520.00-$176,900.00 Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $149,840.00-$187,300.00 Based in the San Francisco Bay area, California: $166,400.00-$208,000.00. This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are generally eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. Applications for this role are intended to be accepted until 11/20/26, but may change based on business needs. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic . Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. . Stay alert to recruitment fraud We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @ twilio.com email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps. . Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.

Location: San Francisco WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW We’re looking for an experienced, hands-on Field Marketing Manager to own and execute our field marketing strategy. This role blends best-in-class tactical execution with strategic planning and operational rigor. You’ll lead the planning and delivery of first-party and third-party events, regional activations, and integrated campaigns designed to drive pipeline, lead generation, and revenue impact across the US market. This is an individual contributor role for a self-starter who thrives in a fast-paced, evolving environment and partners closely with GTM. You’ll be expected to build programs and processes from the ground up, continuously iterate and improve how we operate, and roll up your sleeves to execute—from developing the strategy and playbooks to being on the ground making it happen. WHAT YOU'LL DO - Own the planning and execution of US field marketing programs, including first-party events (executive dinners, roundtables, happy hours, and experiential events) and third-party events (conferences, sponsorships, partner activations). - Design and deliver field marketing initiatives that drive measurable pipeline and lead generation, aligned to regional targets, priority accounts, and GTM objectives. - Partner closely with the US GTM team to develop territory-based and account-focused event strategies, including pre- and post-event engagement and follow-up. - Manage end-to-end event delivery, including budgets, logistics, vendors, agencies, on-site execution, and post-event reporting. - Lead the development of scalable field marketing playbooks, processes, and best practices to support growth and consistency globally. - Own and manage relationships with external agencies, event partners, and third-party organizers, ensuring high-quality delivery and strong ROI. - Track, analyze, and report on the performance of field marketing activities, using data and insights to continuously improve impact and efficiency. WHAT YOU HAVE - 4–7 years of experience in field marketing, event marketing, or demand generation within B2B SaaS or professional services. - Proven ability to deliver high-impact field events and activations that drive measurable pipeline and lead generation. - Strong experience partnering with Sales on territory-based or account-focused marketing initiatives. - Excellent communication, organization, and stakeholder management skills, with a high bar for execution and detail. - Familiarity with tools such as Salesforce, Marketo (or similar), and event platforms is highly desirable. - Experience marketing to legal, financial services, consulting, or other high-touch professional audiences is a plus. COMPENSATION $ 120,000 - $160,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-LT1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: Canada What the Role Is We’re hiring a Staff Software Engineer who’ll be the technical lead for a new Search team at Babylist. This new team will be focused on moving Babylist’s search capability in-house, making our search results more relevant and personalized, and partnering with other teams to transform search in the product from functional to delightful. Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting search and personalization problems in consumer e-commerce. This is zero-to-one work, with big ambitions. You’d build a search capability from the ground up, with a clear mandate from leadership to do it. In your first year, we expect to have rebuilt search to be highly relevant and personalized, and delivered big bets like universal search: one experience across items we sell and items from other retailers, and across products, guides and registries. We also want to work with Addie, our AI registry assistant, to have LLMs play a role in the search experience. If you want to tune an established search system, this isn’t the right role. If you’ve worked inside a strong search team and want to build a new system from scratch at a company earlier in that journey, read on. What You'll Own A Staff Engineer at Babylist sets direction. You’ll be the technical lead for search: you decide where it goes over the next year or two, sequence the bets that get there, and make the technical and product calls along the way. You’re still in the code and will drive initiatives forward across multiple teams. You’ll have software engineering and machine learning engineering support on the team. A few examples of initiatives you’d drive on the Search team: Build search in-house. Choose the architecture for indexing, retrieval and serving, and plan a seamless migration. The system you design replaces what we use today and is the foundation for everything below. Define what a good result is. Decide how we measure result quality, then improve it through query understanding, ranking and the behavioral signals we collect. Unify search across everything we show. One experience across items we sell and items from other retailers, and across products, guides and registries, including how to rank items we don’t sell next to ones we do. Decide how search and recommendations fit together. Bring what we know about a user and their registry into results, and decide how much retrieval and ranking search shares with our recommendation models. Make search conversational. Work with the Addie team, our AI registry assistant, on queries like “best stroller for urban family,” where the shopper describes a need instead of naming a product. Like every Staff Engineer here, you will: Take a fuzzy business problem from the first sketch through to production, and stay on the hook for whether it actually helped customers. Build the platform or tooling other teams adopt by choice, and own it as it scales. Set the standard for how search builds with AI. Decide what good looks like, build the patterns and evals that get agents there and catch the output that's confidently wrong before it ships. Partner with product, design and data as a peer, shaping what's worth building from the start. Coach Senior engineers through the hard calls, the ambiguous ones as much as the technical ones Who You Are You meet the Staff bar at Babylist. You’ve shipped production systems for enough years to have earned strong opinions, and you hold them loosely. You can pick up an ambiguous problem and start moving before anyone hands you the full picture. You’ve already changed how a team builds with AI, and the new way stuck. On top of that, you’ve worked on search problems before, ideally in an e-commerce setting. This role needs depth in the systems behind search and a clear focus on the people using it. You bring: Hands-on search experience: building and running search in production, including indexing, retrieval, ranking and query understanding. You know how to keep a search service fast, relevant and reliable as traffic and catalog size grow. Experience evaluating search quality: offline and online, including relevance judgments and A/B tests. A focus on the user: you use query data, behavior and judgment about result quality to decide what to build, and you can connect a search change to what shoppers do, and to conversion or revenue. Comfort building from zero: you can define the problem, design the system and own it end to end. You measure yourself by impact: a customer outcome, or a system a dozen teams come to depend on. Compensation We post real numbers. For a Canada-based Staff Engineer, the starting base salary range is $299,300 to $372,600 CAD, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $359,160 to $447,120 CAD. On top of that you get meaningful equity and an RRSP match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope. How We Build AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers. The Stack Core app: Rails, Packwerk, React, TypeScript, Sidekiq Mobile: iOS (Swift), Android (Kotlin) Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly Key integrations: Shopify (payments), Iterable (CRM) Why Babylist An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done. Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide. How We Work Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis. How We Hire Three rounds, usually two to three weeks start to finish. Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote. Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles. Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours. Benefits Company-paid medical and fully covered dental and vision A 401(k) match Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program Winter Wonder Week, a paid company-wide week off at the end of the year A remote-work stipend Mental-health and wellness support A Few Things to Know We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws. We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking. If you have a family member or close relationship with a Babylist employee, let your recruiter know. Official outreach only ever comes from an @babylist.com address

Location: Remote, India GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. About the Team GitLab's APJ Ecosystem team builds and scales the partner (channel, alliance, and hyperscaler) motion across the region. India is a strategic market for GitLab, and this hire is central to strengthening our partner ecosystem there — deepening a smaller number of high-value partnerships rather than spreading thin across many transactional ones. About the Role The Scale Ecosystem Sales Manager (ESM), India is a senior, market-facing role responsible for building and scaling GitLab's partner business in India across the full breadth of the ecosystem. This role focuses on new logo acquisition and aligns closely with our new business team in India. This will involve working with  hyperscalers, India-centric system integrators (SIs), and born-in-the-cloud / AI-native partners. We are looking for someone with the range and seniority to credibly own strategic partner relationships across all of these partner types, and to help grow our business through these partners. This is a senior individual-contributor role for someone who has already built a career scaling partner-sourced and influenced revenue in India — someone who knows the hyperscaler ecosystem (AWS & GCP), has deep, credible relationships with India's major SIs, and understands how to engage newer-generation cloud-native and AI partners as they become an increasingly important part of the go-to-market. What You'll Do Build and scale GitLab's partner-sourced and influence business in India across hyperscalers, large India-centric SIs, and born-in-the-cloud/AI partners. Develop deep, strategic (not transactional) relationships with a focused set of priority partners — joint business plans, QBRs, and named executive sponsorship. Own hyperscaler relationship management and Marketplace motion with AWS and/OR GCP. Build and grow relationships with major India SIs and market-making channel/born-in-the-cloud partners and emerging AI-native partners. Drive partner-sourced pipeline and bookings, and carry a quota tied to partner-sourced/generated revenue. Partner closely with the India sales team to ensure partner-sourced opportunities are properly identified, supported, and closed. Work with the India and APJ Ecosystem team to help shape and refine the India Ecosystem coverage model. Contribute to partner enablement, certification, and go-to-market programs suited to the India market. Report on partner engagement health, pipeline contribution, and progress against strategic-partner milestones. What We're Looking For 15+ years of experience in channel/alliance/partner management or ecosystem sales, ideally within enterprise software, DevOps, or cloud infrastructure. Extensive, well-rounded experience scaling a business through partners across hyperscalers, large India-centric SIs, and born-in-the-cloud/AI-native partners — not narrowly specialized in just one partner type. Direct experience managing hyperscaler relationships (AWS, GCP, and/or Azure) including Marketplace motion. A strong, credible existing network among India's major SIs and cloud-native/channel partners, with a track record of moving relationships from transactional to strategic. Comfort carrying a partner-sourced revenue quota and being measured on pipeline origination, not just deal closure. Strong stakeholder management skills — able to align internal sales, marketing, and partner-side stakeholders around joint goals. Native or business-fluent Hindi and strong business English (for regional collaboration with APJ leadership). Based in or willing to relocate to Mumbai OR Delhi. Nice to Have Prior experience at or with a hyperscaler (AWS, GCP) in a partner or alliances capacity. Familiarity with GitLab, DevSecOps, or adjacent developer-tooling ecosystems. Experience helping design or reset a partner coverage model, comfortable building process rather than only inheriting one. What Success Looks Like (First 6–12 Months) Joint business plans and an active engagement cadence (e.g., QBRs) in place across priority hyperscaler, SI, and cloud-native/AI partners. Demonstrable movement of key partner relationships from transactional to strategic engagement. Growing partner-sourced pipeline and bookings against quota. Credible input into finalizing the India Ecosystem coverage model, grounded in on-the-ground partner relationships. How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: Englewood Cliffs, NJ Step into the innovative world of LG Electronics. As a global leader in technology, LG Electronics is dedicated to creating innovative solutions for a better life. Our brand promise, 'Life's Good', embodies our commitment to ensuring a happier life for all. We have a rich history spanning over six decades and a global presence in over 290 locations.  Our diverse portfolio includes Home Appliance Solutions, Media Entertainment Solutions, Vehicle Solutions, and Eco Solutions.  Our management philosophy, "Jeong-do Management," embodies our commitment to high ethical standards and transparent operations. Grounded in the principles of 'Customer-Value Creation' and 'People-Oriented Management', these values shape our corporate culture, fostering creativity, diversity, and integrity. At LG, we believe in the power of collective wisdom through an inclusive work environment.  Join us and become a part of a company that is shaping the future of technology.  At LG, we strive to make Life Good for Everyone. Position Overview We are seeking a strategic and highly collaborative AX Business Liaison to serve as a primary change agent within the organization. The primary role of the AX Business Liaison is to spearhead Business Innovation and Change Management. You will work directly with our domain experts to reimagine legacy processes and transform the way people work to accommodate new, AI-influenced workflows. Sitting at the core of our execution layer within a dedicated AX POD, you will serve as the crucial bridge between business stakeholders and our technical execution teams. You will ensure that the AI solutions we build are not only technically sound but also operationally practical, responsibly implemented, and paired with the operational changes necessary to drive true business value and seamless user adoption. Key Responsibilities 1. Business Innovation & Workflow Transformation (Primary Focus) ● Analyze current business operations to identify bottlenecks, manual steps, and improvement opportunities before applying AI. ● Document current-state and future-state workflows, redesigning processes to natively integrate AI tools, automation, and new decision-support models. ● Challenge the status quo by guiding business leaders away from “how we've always done it” toward AI-augmented operating models, rather than layering new tools onto outdated processes. 2. Change Management & AI Adoption ● Develop and execute comprehensive change management strategies to ensure business units successfully transition to new AI-driven workflows. ● Proactively identify and manage organizational resistance to change, acting as a coach and advocate for AI adoption by helping leaders and users understand how AI will change work. ● Identify, train, and coach business champions in each assigned domain as partners in Business Innovation engagements. ● Equip champions to act as on-the-ground change leads who co-own adoption within their teams, while ADX continues to lead the Business Innovation methodology. 3. Business-to-Technical Translation & Intake ● Partner with business leaders to identify, scope, and define opportunities where AX (AI/Data) solutions can improve operational performance. ● Recommend when a business challenge calls for process redesign or simplification rather than an AI solution. ● Translate redesigned processes into clear technical requirements, user stories, business rules, and acceptance criteria for AX Engineering and Data teams. ● Align pod intake with the guidelines set by the AX PMO's Intake & Metrics team. 4. Responsible AI & Governance ● Work with technical teams to identify and address business-side risks related to bias, data quality, transparency, and operational misuse. ● Embed human-in-the-loop principles into workflow design, ensuring AI workflows are introduced with appropriate business controls and oversight mechanisms. 5. Business Innovation Methodology & Playbook ● Contribute to ADX's Business Innovation playbook by standardizing artifacts and capturing lessons from each engagement. ● Help assigned domains progress through the Business Innovation capability stages on the AX roadmap. Qualifications ● Experience: 5+ years in Change Management, Business Innovation, Process Improvement, Business Transformation, or Product Management. ● Transformation Expertise: Proven track record driving Digital Transformation (DX) initiatives and managing the human side of organizational change. Familiarity with change management frameworks is highly preferred. ● Business Innovation Craft: Hands-on experience with process mapping, workflow analysis, and workshop facilitation. ● Domain Knowledge: Foundational understanding of AI, Machine Learning, and software development lifecycles, with the ability to envision how these technologies change workflows, decision rights, and risk controls. Familiarity with responsible AI concepts. ● Communication & Empathy: Exceptional communication skills and high emotional intelligence. Able to guide non-technical teams through disruptive change while articulating clear workflows to engineering teams. ● Collaboration: Proven experience in a matrixed or pod-based organization, influencing without direct authority across business, project management, and engineering teams. ● Preferred Experience: Internal consulting or transformation office experience, building credibility with business units as a partner from outside the team, is a strong plus. What Success Looks Like in Year One ● Led Business Innovation engagements end to end, with documented future-state workflows in place before build begins on assigned pod initiatives. ● Trained and activated business champions in each assigned domain. ● Achieved strong user adoption, fewer manual workarounds, and positive sentiment for newly deployed AX tools, measured at defined intervals after launch. ● Delivered measurable improvements in cycle time and productivity on deployed initiatives. ● Contributed reusable artifacts and lessons to ADX's Business Innovation playbook. ● Established yourself as a trusted advisor to business leaders on the cultural, operational, and workflow shifts that AI transformation requires. #LI-DR1 Recruiting Range $145,000 — $185,000 USD Benefits Offered Full-Time Employees: No-cost employee premiums for you and your eligible dependents for competitive medical, dental, vision and prescription benefits. Auto enrollment with immediate vesting of competitive company matching contributions in a 401(k) Retirement Savings Plan with several investment options. Generous Paid Time Off program that includes company holidays and a combined bank of paid sick and vacation time. Performance based Short-Term Incentives (varies by role). Access to confidential mental health resources to help you and your loved ones improve your quality of life. Personal fitness goal incentives. Family orientated benefits such as paid parental leave and support for families raising children with learning, social, behavioral challenges, or developmental disabilities. Group Rate Life and Disability Insurance. Benefits Offered Temporary/Contractors: Eligible for the relevant benefit programs offered through our partner agencies. Privacy Notice to California Applicants Applicants who need assistance or a reasonable accommodation during the hiring process may contact our team by phone at: 973-477-7090 or support@lg4me.freshdesk.com. This email and phone number will only reply to accommodation requests and is not intended for general employment inquiries. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. In addition to the above, LG believes that pay transparency is a key part of diversity, equity, and inclusion. Our salary ranges take into account many factors in making compensation decisions including but not limited to skillset, experience, licensure, certifications, internal equity, and other business needs. While we consider geographic pay differentials in final offers, because we operate in many geographies where applicable, the salary range listed may not reflect all geographic differentials applied .

Location: Alpharetta, GA Step into the innovative world of LG Electronics. As a global leader in technology, LG Electronics is dedicated to creating innovative solutions for a better life. Our brand promise, 'Life's Good', embodies our commitment to ensuring a happier life for all. We have a rich history spanning over six decades and a global presence in over 290 locations.  Our diverse portfolio includes Home Appliance Solutions, Media Entertainment Solutions, Vehicle Solutions, and Eco Solutions.  Our management philosophy, "Jeong-do Management," embodies our commitment to high ethical standards and transparent operations. Grounded in the principles of 'Customer-Value Creation' and 'People-Oriented Management', these values shape our corporate culture, fostering creativity, diversity, and integrity. At LG, we believe in the power of collective wisdom through an inclusive work environment.  Join us and become a part of a company that is shaping the future of technology.  At LG, we strive to make Life Good for Everyone. Technical Training Content Developer The Technical Training Content Developer is responsible for designing and developing engaging digital learning content that supports technical training initiatives for LG HVAC products and systems. This role focuses primarily on eLearning development, microlearning, video-based learning, and multimedia content creation. Working closely with instructional designers and subject matter experts (SMEs), the Technical Training Content Developer transforms complex technical information into effective, learner-focused training solutions. Responsibilities Develop eLearning modules, microlearning content, and video-based training materials. Create and edit instructional videos, graphics, animations, and other multimedia assets. Collaborate with SMEs and instructional designers to convert technical information into engaging learning experiences. Develop and maintain digital training content aligned with product launches, technical updates, and business priorities. Support the creation and revision of instructor-led training materials as needed. Manage multiple projects while meeting established deadlines and quality standards. Qualifications Bachelor's degree in Instructional Design, Education, Multimedia Design, Communications, or a related field. 5-7 years of experience developing technical training content in HVAC, manufacturing, industrial, or other technical environments. Experience developing eLearning, microlearning, and video-based learning content. Proficiency with Articulate Storyline, Rise, or similar eLearning authoring tools. Strong proficiency with Adobe Creative Cloud, including Premiere Pro and Photoshop. Experience creating and editing instructional videos and multimedia learning assets. Strong written communication, visual design, and content development skills. Ability to work effectively with technical subject matter experts. Preferred Qualifications Experience in the HVAC industry. Experience developing training content for manufacturing, technical products, industrial equipment, or related technologies. Experience with Adobe After Effects and Illustrator. Familiarity with Learning Management Systems (LMS). Knowledge of adult learning principles and instructional design best practices. #LI-DB2 Recruiting Range $40 — $40 USD Benefits Offered Full-Time Employees: No-cost employee premiums for you and your eligible dependents for competitive medical, dental, vision and prescription benefits. Auto enrollment with immediate vesting of competitive company matching contributions in a 401(k) Retirement Savings Plan with several investment options. Generous Paid Time Off program that includes company holidays and a combined bank of paid sick and vacation time. Performance based Short-Term Incentives (varies by role). Access to confidential mental health resources to help you and your loved ones improve your quality of life. Personal fitness goal incentives. Family orientated benefits such as paid parental leave and support for families raising children with learning, social, behavioral challenges, or developmental disabilities. Group Rate Life and Disability Insurance. Benefits Offered Temporary/Contractors: Eligible for the relevant benefit programs offered through our partner agencies. Privacy Notice to California Applicants Applicants who need assistance or a reasonable accommodation during the hiring process may contact our team by phone at: 973-477-7090 or support@lg4me.freshdesk.com. This email and phone number will only reply to accommodation requests and is not intended for general employment inquiries. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. In addition to the above, LG believes that pay transparency is a key part of diversity, equity, and inclusion. Our salary ranges take into account many factors in making compensation decisions including but not limited to skillset, experience, licensure, certifications, internal equity, and other business needs. While we consider geographic pay differentials in final offers, because we operate in many geographies where applicable, the salary range listed may not reflect all geographic differentials applied .

Location: Santa Clara Forward was founded in 2013 by four Stanford Ph.D.s, building the industry's first network digital twin: a mathematically accurate model of the production network. It's the foundation for autonomous networking, giving engineers and AI agents the ability to know the impact of every change before it touches production. That founding instinct still defines how we work. We're accurate and evidence-driven, relentless about clarity, and we'd rather be certain than comfortable, building a groundbreaking platform that transforms how teams run and secure networks across every major cloud and vendor environment. Global leaders like Goldman Sachs, PayPal, S&P Global, IBM, and Dell trust Forward, alongside fast-growing enterprises and government agencies, realizing an average of $14.2 million in annual benefits, according to IDC. Backed by top-tier investors, including A. Capital, Andreessen Horowitz, Goldman Sachs, MSD Partners, Omega Venture Partners, Section 32, and Threshold Ventures, and headquartered in Santa Clara, we're most proud of our team: curious people who'd rather build what doesn't exist than accept how things have always been done. About the Role We are looking for a HR Business Partner (HRBP) to serve as a strategic partner to our Engineering organization. This role sits at the intersection of business strategy and people strategy, working directly with senior engineering leaders (VPs, Directors, and Engineering Managers) to build high-performing teams, shape organizational design, and drive talent, culture, and change initiatives that scale with a fast-moving technology organization. This role requires deep credibility with technical audiences and a strong point of view on what great engineering culture looks like. What You'll Do Serve as a trusted strategic advisor to Engineering senior leadership, providing coaching and counsel on organizational design, workforce planning, leadership effectiveness, and team dynamics. Partner with engineering leaders to translate business and technical roadmaps into people strategies, including org design, span of control, and role architecture as the organization scales. Lead full-cycle talent management for the client group: performance management, calibration, succession planning, promotion processes, and career development frameworks tailored to engineering career ladders (IC and management tracks). Use data and analytics (attrition, engagement, hiring velocity, promotion equity, span of control) to diagnose organizational health and recommend proactive interventions. Partner closely with Talent Acquisition to inform hiring strategy, headcount planning, and workforce composition for engineering. Lead or co-lead org design and change management efforts tied to reorganizations, M&A integration, or rapid scaling. Coach engineering managers and directors on leadership skills, difficult conversations, team performance, and conflict resolution. Drive compensation planning cycles (merit, equity refresh, promotions) in partnership with Total Rewards, ensuring internal equity and market competitiveness for technical roles. Own employee relations matters within the client group, ensuring fair, consistent, and legally sound resolution of issues. Champion diversity, equity, and inclusion initiatives specific to the challenges of building diverse technical teams. Partner cross-functionally (Talent Acquisition, L&D, Legal) to design and deliver programs that meet the unique needs of engineering. Act as a culture carrier, helping engineering leaders build and reinforce an environment of technical excellence, psychological safety, and inclusion. What We're Looking For 7–10+ years of progressive HR Business Partner experience, with a significant portion spent directly supporting Engineering, R&D, or other highly technical client groups. Proven experience operating at a senior level, partnering directly with VP- and Director-level engineering leaders. Deep understanding of engineering organizational structures, career ladders (IC vs. management tracks), and the specific talent dynamics of technical hiring and retention. Strong track record leading org design, workforce planning, and change management in a fast-paced, high-growth, or scaling technology environment. Excellent coaching skills with the credibility and presence to influence senior technical leaders. Data-driven approach to HR — comfortable building and interpreting people analytics dashboards to inform decisions. Sound judgment and experience navigating complex employee relations issues; working knowledge of employment law. Experience leading or contributing to compensation cycles, including equity compensation, for technical roles. Exceptional communication, influencing, and relationship-building skills across all levels of the organization. Bachelor's degree required; advanced degree (MBA, HR, Organizational Psychology) or SHRM-SCP/SPHR certification a plus. The base pay range for this role is between $210,000 and $265,000. Base pay will depend on your skills, qualifications, experience. This is a regular, in office full-time position with Forward.  We are currently in office two days per week (Tuesday/Thursday) Location : Santa Clara, California

Location: Remote USA Forward was founded in 2013 by four Stanford Ph.D.s, building the industry's first network digital twin: a mathematically accurate model of the production network. It's the foundation for autonomous networking, giving engineers and AI agents the ability to know the impact of every change before it touches production. That founding instinct still defines how we work. We're accurate and evidence-driven, relentless about clarity, and we'd rather be certain than comfortable, building a groundbreaking platform that transforms how teams run and secure networks across every major cloud and vendor environment. Global leaders like Goldman Sachs, PayPal, S&P Global, IBM, and Dell trust Forward, alongside fast-growing enterprises and government agencies, realizing an average of $14.2 million in annual benefits, according to IDC. Backed by top-tier investors, including A. Capital, Andreessen Horowitz, Goldman Sachs, MSD Partners, Omega Venture Partners, Section 32, and Threshold Ventures, and headquartered in Santa Clara, we're most proud of our team: curious people who'd rather build what doesn't exist than accept how things have always been done. About the Role Forward is looking for a HR Business Partner (HRBP) to serve as a strategic partner to our Sales organization. This role sits at the intersection of business strategy and people strategy, working directly with senior sales leaders (CRO, VPs of Sales, and Regional/Sales Directors) to build high-performing revenue teams, shape organizational design, and drive talent, culture, and change initiatives that scale with an evolving go-to-market motion. This role requires deep credibility with commercial leaders and fluency in the unique dynamics of a quota-carrying, commission-driven workforce. What You'll Do Serve as a trusted strategic advisor to Sales senior leadership, providing coaching and counsel on organizational design, territory/quota structure, workforce planning, and leadership effectiveness. Partner with sales leaders to translate revenue targets and go-to-market strategy into people strategies, including org design, span of control, and role architecture as the sales org scales or restructures. Lead full-cycle talent management for the client group: performance management, calibration, succession planning, promotion processes, and career pathing tailored to sales career ladders (RSD/AE, SDR/BDR, sales management, and sales enablement tracks). Use data and analytics (attrition, ramp time, quota attainment, rep productivity, pipeline health as it relates to headcount, promotion equity) to diagnose organizational health and recommend proactive interventions. Partner closely with Talent Acquisition on sales-specific hiring strategy, headcount planning, and workforce composition, including seasonal/quarterly hiring cycles tied to sales capacity planning. Lead or co-lead org design and change management efforts tied to territory realignments, reorganizations, M&A integration, or new market/segment launches. Coach sales managers and directors on leadership skills, performance conversations, managing underperformance in a quota-driven environment, and team motivation. Partner with Compensation on commission plan design, quota setting implications, and annual compensation planning cycles (merit, equity, promotions) to ensure competitiveness and pay-for-performance alignment. Own employee relations matters within the client group, including performance improvement plans and terminations tied to quota non-attainment, ensuring fair, consistent, and legally sound resolution. Champion diversity, equity, and inclusion initiatives specific to the challenges of building diverse sales teams. Partner cross-functionally (Talent Acquisition, Legal, Sales Enablement) to design and deliver programs that meet the unique needs of a revenue organization. Act as a culture carrier, helping sales leaders build and reinforce an environment of high performance, accountability, and inclusion. What We're Looking For 7–10+ years of progressive HR Business Partner experience, with a significant portion spent directly supporting Sales, Revenue, or other quota-carrying/commission-based client groups. Proven experience operating at a senior level, partnering directly with CRO, VP, and Director-level sales leaders. Deep understanding of sales organizational structures, compensation plan design (base/commission/OTE), quota methodology, and the specific talent dynamics of hiring and retaining sales talent. Strong track record leading org design, workforce planning, and change management in a fast-paced, target-driven, high-growth environment. Excellent coaching skills with the credibility and presence to influence senior commercial leaders. Data-driven approach to HR — comfortable building and interpreting people analytics dashboards (attrition, ramp, productivity) to inform decisions. Sound judgment and experience navigating complex employee relations issues, including performance-based terminations; working knowledge of employment law. Experience partnering on incentive compensation design and annual compensation planning cycles. Exceptional communication, influencing, and relationship-building skills across all levels of the organization. Bachelor's degree required; advanced degree (MBA, HR, Organizational Psychology) or SHRM-SCP/SPHR certification a plus. The base pay range for this role is between $210,000 and $265,000. Base pay will depend on your skills, qualifications, experience, and location

Location: United States, San Mateo, CA Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Senior Director, Strategic Development Position Overview Sony Interactive Entertainment is entering an important new chapter in its evolution looking to expand business and identify future growth opportunities. This is a senior leadership position for an individual who combines exceptional strategic judgment with the ability to activate change across complex, highly accomplished organizations. The successful candidate will help SIE move beyond strategy as an annual planning exercise toward a continuous discipline of strategic choices, organizational alignment, experimentation, and measurable business outcomes. Working directly within the Business Strategy team alongside senior leaders across PlayStation, this individual will build the frameworks, decision mechanisms, and leadership practices that enable executives to own the outcomes of the company's strategic evolution. The central purpose of this role is not simply to develop strategy. It is to help the organization become better at continuously making, activating, and adapting strategic decisions. Key Responsibilities Activate PlayStation's Strategic Transformation Translate PlayStation's long-range strategic direction into clear, actionable enterprise priorities that connect the company's existing strengths with future growth opportunities. Help operationalize the strategic shifts defining PlayStation's evolution, including developing new value propositions, driving business model adaptation to new customers and opportunities and moving from periodic planning to continuous strategic adaptation. Establish practical frameworks that clarify what SIE must preserve, evolve, and newly develop over the next three to five years. Partner with functional executives to translate enterprise strategy into meaningful choices, commitments, and measurable outcomes within their organizations. Identify structural, cultural, and operational barriers to transformation and help leadership teams address them. Activate the strategy by embedding it within cross functional leaders to own it and adapt it as assumptions change. Establish Continuous Strategic Planning and Adaptation Build a strategy capability that operates throughout the year, responding to market shifts, emerging technologies, competitive developments, and organizational learning. Design and implement a continuous strategy operating rhythm, connecting three-to-five-year ambitions with annual priorities, quarterly strategic reviews, and ongoing opportunity assessment. Develop scenario-planning, strategic sensing, and portfolio-evaluation frameworks that allow leadership to anticipate change rather than simply respond to it. Connect insights from product, commercial, finance, technology, studios, and external partners into an evolving view of PlayStation's future. Create the right level of materials for decision-oriented executive forums and then orchestrate those important meetings to find emerging opportunities, challenge assumptions, and recommend adjustments to strategic priorities. Build mechanisms for leaders to revisit investment assumptions and reallocate attention and resources as evidence changes. Influence and Mobilize Cross-Functional Executive Leadership Serve as a trusted strategic partner to senior leaders, bringing together different perspectives and enabling collective decisions on issues that transcend individual business units. Build trusted relationships with VP- and SVP-level leaders across PlayStation and Sony Group. Facilitate high-stakes strategic conversations involving competing priorities, resource constraints, and differing perspectives on the future. Use rigorous analysis (both internal and external), commercial judgment, and compelling narratives to influence decisions without relying on formal authority. Help executive teams move from conceptual agreement to explicit decisions, accountable ownership, and coordinated action. Challenge established assumptions constructively while demonstrating respect for the achievements and operational realities of existing businesses. Identify and resolve strategic misalignment before it becomes an impediment to execution. Develop the Core / Explore Strategic Framework Support the development of two distinct but interconnected operating models that allow PlayStation to maximize current business performance while investing in future opportunities. Establish differentiated frameworks for evaluating core-business optimization and higher-uncertainty exploration initiatives. Help define how future opportunities are identified, validated, incubated, prioritized, and transitioned into scaled operating businesses. Partner with Finance and operating leaders to develop portfolio-level investment frameworks that balance near-term returns with longer-term strategic value. Create transparent decision criteria for advancing, redirecting, or discontinuing strategic initiatives. Ensure exploration activities are commercially grounded without subjecting early-stage opportunities to inappropriate mature-business performance expectations. Support leadership in determining where shared capabilities, resources, and partnerships can accelerate both operating systems. Strengthen Enterprise Strategy Execution and Organizational Capability Create repeatable approaches that allow SIE leaders to turn strategic direction into coordinated organizational progress. Develop executive-level strategy activation frameworks, including strategic outcome maps, decision rights, leadership commitments, and progress measures. Partner with team members to create processes for translating strategic choices into functional priorities without creating unnecessary reporting or bureaucracy. Facilitate leadership working sessions that resolve trade-offs and create durable ownership of agreed outcomes. Build strategy toolkits and practical methodologies that functional teams can adopt independently. Capture and institutionalize lessons from strategic initiatives, including successes, unsuccessful experiments, and changing market assumptions. Introduce AI-enabled research, synthesis, scenario modeling, and knowledge-management capabilities that increase the speed and quality of strategic work. Required Experience and Qualifications The ideal candidate will bring 15+ years of progressive experience in enterprise strategy, business transformation, corporate development, strategic operations, or product leadership, including substantial experience influencing senior executives within complex global organizations. A proven record of leading enterprise-wide strategic transformation, with tangible examples of changes adopted by business leaders and sustained beyond the initial initiative. Deep experience influencing cross-functional leadership teams, particularly in situations involving ambiguous authority, competing priorities, and significant organizational complexity. Demonstrated success designing and implementing strategic planning, portfolio management, or governance frameworks that improved actual business decisions. Experience in technology platforms, gaming, digital entertainment, consumer ecosystems, or similarly dynamic industries. Strong commercial and financial judgment, including the ability to evaluate investment trade-offs, growth opportunities, and long-range enterprise value. Exceptional executive communication, facilitation, and strategic storytelling capabilities. Experience navigating global organizations and multicultural leadership environments. Demonstrated ability to use emerging AI and analytical capabilities to improve strategic effectiveness. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. The estimated base pay range for this role is listed below. $275,000 — $412,400 USD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

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

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

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

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

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

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

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

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

Location: San Francisco Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW In this role, you'll own how we adapt and improve leading open-weight models for legal work. We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the post-training recipe across SFT and RL, including reward design and verification for challenging, semi-verifiable legal tasks. You’ll help set the research direction and carry ideas from experiments through training runs to models used by customers. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work. We’re looking for research engineers and scientists who have gotten training runs working at scale, are immersed in RL for language models, and want their work to reach users quickly. Learn more about our work at harvey.ai/research http://harvey.ai/research. WHAT YOU'LL DO - Own and pursue a research agenda to improve model capability on long-horizon legal reasoning and agentic workflows. - Design and run post-training experiments across SFT and RL, building on leading open-weight models. - Develop reward functions and verifiers for semi-verifiable tasks, including rubrics, learned preference models, and expert preference data, and study where they break. - Run and debug training at scale, addressing divergence, reward hacking, and instability. - Build and use rigorous evals to track improvements and decide what ships. - Design, implement, test, and debug code across our research stack. WHAT YOU HAVE - Hands-on experience post-training LLMs with SFT and RL, including preference optimization, and direct ownership of training runs and results. - Deep ML fundamentals and experience getting distributed training runs working reliably. - Strong engineering skills in Python, with production-quality code and end-to-end system ownership. - Research experience in RL for language models or reward modeling, with the ability to move quickly from experiments to shipped improvements. Publications welcome, not required. We are hiring for this role across multiple levels. COMPENSATION $230,000 - $450,000 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-DZ1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai