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Location: Boston, MA Workplace: OnSite At WHOOP, we’re on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies, behaviors, and daily lives.   WHOOP Labs is the on-site research facility for product development and innovation at WHOOP. We conduct human-centered hardware and algorithm research to create best-in-class product experiences that work for all members.   WHOOP is hiring a Researcher II to support research planning and execution on weekends, supporting critical data collection windows for participant diversity and expanded access. This role will cover a broad range of research studies for algorithm training, hardware validation, and design testing. While your home base will be WHOOP’s on-site product research facility, WHOOP Labs, studies will include field collections across the metro Boston area to widen access for diverse communities. Your efforts will support the organization as we continue to develop a best-in-class experience and lead the wearables industry.   *This role is fully onsite at our Boston, MA office and follows a 4x10 schedule, with four 10-hour workdays each week, Friday through Monday, and three days off Tuesday through Thursday.   RESPONSIBILITIES - Execute testing protocols across multiple concurrent studies, owning research execution on weekends and collaborating with other researchers on Friday and Monday to ensure consistent protocol administration across all days and shifts. - Own research documentation for weekend hours, collaborating with other researchers on Friday and Monday to ensure effective handoffs and information transfer across shifts. - Provide coaching and guidance to participants during exercise protocols, balancing data integrity, research best practices, and participant experience - Create a supportive and welcoming environment for participants engaging in a range of research tasks, from exercises to device interactions - Manage the use, troubleshooting, and upkeep of sensitive data collection equipment and prototype devices - Develop strong working knowledge of WHOOP’s research platform tooling suite, with the ability to troubleshoot issues in real time—including during active data collections—and problem-solve on the fly - Develop junior researchers by providing technical coaching, delegation, constructive feedback, and growth opportunities - Own daily lab management tasks required for data collections to be successful, such as laundry, equipment cleaning, material organization, and overall lab readiness - Serve as an ambassador for WHOOP Labs and the WHOOP brand   QUALIFICATIONS - Bachelor’s Degree in human physiology, biomedical engineering, psychology, HCI, or similar - Professional experience in research & development, human subjects research, or a related field, including 2+ years of experience conducting human subjects research - Strong technological background and working knowledge of data management systems including the Google Suite - Familiarity with research platform tools and hardware testing environments preferred - Strong interpersonal communication skills with a savvy for working as part of a highly collaborative, fast-paced team - Ability to manage multiple priorities and adapt quickly in dynamic research settings - Prior experience in customer service or other public-facing roles a plus - Strong written, verbal, and presentation skills, with confidence giving and receiving feedback across disciplines   Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success. The U.S. base salary range for this full-time position is $75,000 - $95,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

Location: Vancouver, BC Our work informs teams at every level of Asana and drives key roadmap decisions. We partner with Product Design, Product Management, Data Science, and Engineering, as well as business and marketing teams, to develop valuable insights about customer behaviors and attitudes, translating them into actionable recommendations. We think deeply about new areas, help develop and test concepts, and improve products and services once they’ve rolled out. As a Senior Experience Researcher, you will be a strategic partner who not only executes high-impact research but also shapes the research culture to elevate our collective craft. This role is based in our Vancouver office. Day to day collaboration is split roughly 50/50 between Vancouver teammates and San Francisco teammates. Locally, you will work closely with our PLG Adoption teams, specifically partnering with the AI Activations (AIA) and Conversion and Retention (CoRe) teams. Key local partners include Product Managers, Designers, and Engineering leads. We operate with an office-centric hybrid schedule. In-office days are Monday, Tuesday and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you interview for this role, your recruiter will share more about in-office requirements. In this role, you will help shape and scale Asana’s Product-Led Growth (PLG) self-serve business. We recently launched several major new products—including AI Teammates, a Meetings product, and Asana for Client Management (ACM). We are also preparing two more major product lines for launch, which will unlock entirely new workflows and use cases for our customers.  Historically, our growth relied on selling more seats or moving customers to higher tiers. Now, we have multiple new growth vectors, from AI credit consumption to these brand new product offerings. You will play a pivotal role in uncovering how to introduce users to these products, encourage users to try them, adopt them into their daily workflows, and deepen their usage over time. The Experience Researcher plays a key role in defining the product roadmap and influencing how our PLG adoption strategy evolves. What you’ll achieve In your first 4-5 months, you will partner with Adoption teams on immediate Q4 roadmap priorities, building out the self-serve pathways to buy and adopt our newest products. Over time, your remit will expand as we roll out self-serve motions for additional products. Be a strategic partner: Together with your cross-functional partners (Product, Design, Engineering, Data Science) you’ll uncover how to best introduce users to Asana’s new products, encourage users to try them out, drive adoption in daily workflows, and deepen usage over time. Drive ACM self serve growth: Research how users discover Asana for Client Management (ACM), start using it, adopt advanced features, and expand its footprint across their organization. Uncover opportunities and pathways for how AI teammates, the Meetings product, and the client portal help customers extract more value from ACM and invite cross-functional collaboration. Lead research on new concepts: Lead research on new concepts: Drive exploratory and evaluative research for upcoming product additions, assessing whether new concepts and personalized experiences feel valuable enough to encourage user engagement and organic sharing. Build a foundation for future PLG offerings: Identify high-impact research needs to support the self-serve rollouts for the next two major product launches. Connect insights to business impact: Ensure research directly influences the roadmap to meet critical business metrics, supporting our goals for AI ARR growth, higher-LTV customers, and increased NRR. About you 6+ years of experience practicing UX Research for digital products, with a proven track record of leading large-scale projects. Strong proficiency in mixed-methods research , seamlessly combining qualitative deep-dives (contextual inquiry, prototype testing) with quantitative validation (survey design, behavioral data analysis) to triangulate insights and build high-confidence recommendations. Mature product judgement with the ability to distill messy signal into clear, "low-polish" deliverables that drive immediate decision-making. Strong organizational leadership and the ability to manage multiple complex workstreams while building deep trust and rapport with senior stakeholders. Deep understanding of interaction design and content hierarchy, allowing you to partner effectively with Design and Content Strategy to reduce friction and drive user action. Persuasive communicator who can influence product strategy through storytelling and evidence-based recommendations. Actively experimenting with AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making. We’re looking for researchers who can harness AI to extend and deepen the ways in which we develop insights and leverage them across the org. What we’ll offer Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. Estimated Base Salary Range: $132,000- $178,000 Equity and Benefits: Compensation includes equity and a comprehensive benefits package. Well-being: Mental health, wellness & fitness benefits, and inclusive family-building support. Growth: Career coaching and professional development support. Culinary: In-office culinary options tailored to your dietary preferences. Future: Long-term savings and retirement plans. About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law. Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

Location: London DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. Fundamental Researcher - Compute Markets The role DRW is seeking a Fundamental Researcher to develop investment views on compute markets and the infrastructure that supports them. You will research the economics of compute supply and demand, form views on the macro forces shaping the market, and translate them into investment recommendations for a compute derivatives strategy. You will work alongside a quantitative researcher who owns the pricing models. Your contribution is an independent, fundamental perspective: understanding the models well enough to test their assumptions against what is happening in the market, and flagging when the market has moved ahead of them. This is a founding seat on a small investment team. We are particularly interested in candidates with credit, commodities or semiconductor research experience who can apply rigorous analysis of cash flows, capacity, contracts and downside risk to a market that is still taking shape. We do not expect deep prior experience in compute. We expect strong analytical foundations and the curiosity to build sector expertise quickly. What you'll do Develop macro and fundamental views on compute. Track and interpret the forces driving supply and demand: AI training and inference demand, hyperscaler and neocloud capital expenditure, chip supply and generational transitions, data center capacity, power availability, financing conditions and policy, including export controls. Translate pricing into investment views. Assess what compute pricing across contract terms and chip generations implies about demand, capacity and scarcity. Identify where prices diverge from fundamentals and recommend how to express those views. Validate pricing assumptions. Develop a working understanding of the pricing models and supply the fundamental evidence behind their key inputs, including supply pipeline, utilization, workload mix and the pace of price declines across hardware generations. Challenge those inputs when the evidence changes. Build research models. Develop supply-and-demand balances, unit economics and scenarios that connect fundamental drivers to compute pricing and investment outcomes, with assumptions documented and testable. Assess counterparties and assets with a credit investor's discipline. Evaluate revenue quality, utilization, cost structure, customer concentration, contractual commitments, leverage, liquidity and refinancing risk. Examine how generational turnover and the falling cost of compute affect asset values, counterparty resilience and recoveries. Make clear recommendations. Present to the Portfolio Manager and Investment Committee, setting out the investment thesis, valuation framework, catalysts, risks and the evidence that would change the view. Build differentiated information sources. Develop a network of industry contacts and data sources across hardware, cloud, data center and power markets to test assumptions and spot inflections early. What we're looking for 5 to 7 years of fundamental investment research experience, ideally in credit research or investing (including structured or asset-backed finance), commodities (particularly power and energy), or buy-side or sell-side coverage of semiconductors and digital infrastructure. A demonstrated ability to turn complex or incomplete information into a clear investment judgment. Strong financial modeling skills and a thorough understanding of cash flow analysis, capital structures and downside scenarios. Enough quantitative fluency to engage with pricing models: understand how they work, interrogate their inputs and judge whether their outputs are consistent with the market. You will not be expected to build or maintain them. An understanding of how a fundamental view translates into a derivatives position such as a forward or swap, or the ability to learn this quickly. The ability to distinguish structural trends from temporary supply-and-demand imbalances and to assess what is already reflected in pricing. A strong interest in compute markets and the drive to build expertise across hardware, cloud services, data centers and power infrastructure. Prior experience in the sector is valuable but not required. Clear written and verbal communication, intellectual independence, and a willingness to challenge assumptions and revise views as evidence changes. For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice . California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice . #LI-JW1

Location: San Francisco, CA • New York, NY • United States Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! The Figma Research team is hiring an experienced researcher to support our core product, Figma Design, and actively shape and execute research to drive scale, tap new opportunities, and ensure Figma continues pushing innovation in design and production tooling. Partnering with Product, Design, and Engineering, you'll bring a deep passion for research and strategy, pushing the envelope with AI-led experiences and laddering key user needs to critical product decisions — tackling our highest impact problems and influencing company strategy for both the short- and long-term. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: Help Figma grow and innovate by delivering strategic research and recommendations and materially influencing the vision and strategy for Figma Design Partner closely with product leaders to identify opportunities, generate strategy, and define success Break down complex business challenges into clear research plans; own the end to end research process and leverage strong storytelling skills to deliver meaningful impact to Figma's businesses Translate research insights into a compelling narrative that shapes product roadmap priorities Advocate for the role of Research as a strategic partner in the business process We'd love to hear from you if you have: 7+ years of experience in UX research or user insights at a high growth B2B SaaS company Expertise in utilizing a variety of research methodologies, including both qualitative and quantitative techniques, to address product challenges spanning from opportunity identification, concept testing, to feature iterations — including research on AI-powered features or products exploring AI applications Demonstrated success in identifying assumptions that underpin key challenges, prioritizing the most critical assumptions, and creating right sized research approaches to test those critical assumptions A proven track record of gaining buy in from executive stakeholders and cross disciplinary partners, transcending mere research mechanics and findings to articulate a larger user story, and the "so what" to inspire action Ability to balance speed, rigor, and competing inputs — pivoting direction, weighing user research, strategy, business insights, and team input in decision-making, and seeking solutions in creative ways While it's not required, it's an added plus if you also have: 2+ years in product design, user centric product management, product development, and/or front end engineering A familiarity and depth of experience using Figma's products At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Pay Transparency Disclosure Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. Figma offers equity to employees, as well as a competitive package of additional benefits, including health, dental, and vision coverage; retirement benefits with company contributions; parental leave and reproductive or family planning support; mental health and wellness benefits; and paid time off. Figma provides paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws, including the requirements of the Washington Minimum Wage Act and related regulations. Exempt employees are eligible for employer‑provided paid flexible PTO in addition to flexible paid sick leave. PTO is subject to manager approval. Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts. Figma also offers sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles. All compensation and benefits are subject to applicable plan terms and may be modified by Figma at any time, consistent with applicable law. Annual Base Salary Range: $169,000 — $250,000 USD At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status , or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com . These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities. Examples of accommodations include but are not limited to: Holding interviews in an accessible location Enabling closed captioning on video conferencing Ensuring all written communication be compatible with screen readers Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice . Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles: Candidates may submit up to 5 applications during any rolling 30-day period. Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection. Once the applicable days has passed, candidates are welcome to apply again.

Location: San Francisco Head of Research Our work informs teams at every level of the company and drives key roadmap decisions. We partner with Product Design, Product Management, Data Science, and Engineering, as well as business and marketing teams, to get deep insights about our customer's behaviors and attitudes, translating them into actionable recommendations across the company. We think big about new areas, test developing concepts, and evaluate products and services once they’ve rolled out. We are looking for a Head of Product Research to lead a high-impact, mixed-method research practice spanning UX Research and Quantitative Market Research (QMR) at a pivotal moment in the company's evolution. In this role, you will build and lead a research function that generates actionable understanding of our users and their unmet needs, partnering across Product, Design, Engineering, and go-to-market teams to ensure insights are heard, applied, and reflected in strategic decisions. This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Define and own the research agenda mapped to our highest-priority product and business questions, setting the standard for how insights translate into decisions from framing through synthesis, storytelling, and follow-through. Champion a mixed-method approach—selecting qualitative, quantitative, or combined methods based on the strategic question—and serve as a thought partner to Design, Product, Data Science, and Engineering leadership. Lead and unify a combined UX Research and Quantitative Market Research (QMR) function, ensuring coordinated methodology and a holistic view of user and market insight. Hire, develop, and retain a high-performing team across experience levels, cultivating a culture of craft, curiosity, accountability, and mentorship. Lead the adoption and operational guidelines of modern AI tools to increase research velocity and coverage without sacrificing rigor. Own the strategy and facilitation of our Beta program to build structured design partnerships with key customers that foster actionable feedback and co-development. Define and maintain a company-wide usability framework embedded into the development process to ensure quality is continuously assessed. Build scalable research operations across tooling, panel management, knowledge management, and recruitment infrastructure to prioritize resources effectively. About you Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making. Proven experience leading and scaling user research teams in a complex product environment, with deep expertise in qualitative and quantitative mixed-method research. Demonstrated track record of connecting user and market insights directly to product strategy, roadmap decisions, and business outcomes. Background navigating complex B2B or B2B2C contexts with multiple user types and cross-functional stakeholder audiences. Strong executive presence with an ability to distill complex findings into clear, compelling narratives for cross-functional leadership. Proven ability to build operational infrastructure, recruitment frameworks, and team structures from the ground up. Familiarity with AI tools and their evolving role within product landscapes and research methodologies. At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply. What we’ll offer Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit. For this role, the estimated base salary range is between $350,000-$425,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified. In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role. We strive to provide equitable and competitive benefits packages that support our employees worldwide and include: Mental health, wellness & fitness benefits Career coaching & support Inclusive family building benefits Long-term savings or retirement plans In-office culinary options to cater to your dietary preferences These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role. #LI-Hybrid About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law. Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

Location: Paris, France; Bordeaux, France; Marseille, France; Brussels, Belgium; Madrid, Spain; Barcelona, Spain Workplace: Hybrid HEALTH CAN’T WAIT. Not for symptoms to get worse. Not for a six‑month appointment. Not for a system to catch up. But that’s exactly how healthcare works today. You wait, until you can’t. Alan exists to end the wait. Health is a universal right, and we believe this right can only become real when it’s coupled with prevention. We need to stop treating health as something we repair and start treating it as something we build, every day. It’s not solely a question of willpower. It’s the healthcare system itself that needs to work for everyone, in a sustainable way. So we are building the new standard in prevention insurance. Alan is the first company that integrates insurance, prevention, and care into a single, acclaimed user experience. We are on an incredible journey to build a global leading company, with a unique culture https://alan.com/en/careers. We already partner with 40K+ companies of all sizes, serving more than 1M+ members, and have reached €800M+ in ARR. Prevention as the new norm. That's what we're building with our team of 1000+ people. If it speaks to you: we're hiring across France, Spain, Belgium, and Canada. And beyond. ⭐️ THE USER RESEARCHER ROLE ⭐️ At Alan, research is not a checkpoint. It's a compass. Our User Research team sits at the intersection of product, design, and engineering, making sure every decision is grounded in what our members actually need, feel, and experience. As a User Researcher at Alan, you will gather and prioritize the most important questions from across the company, and design the right research to answer them. That means running interviews, diary studies, surveys, and usability sessions throughout the full product cycle, not just at the end. You'll then turn those findings into insights that are clear, compelling, and genuinely useful to the teams who need them. You'll work hand in hand with Product Managers, Designers, and Engineers, and collaborate closely with our analytics and data science teams to tell a complete story about our product. You'll also help grow research culture across Alan, sharing your craft and mentoring teammates along the way. At Alan, great research drives great product. If you love figuring out what people truly need and translating that into decisions that matter, this role is for you. ⭐️ IF YOU HAVE SOME OF THE FOLLOWING, YOU MAY BE A GREAT FIT ⭐️ You may be a great fit at Alan if you have: - 4+ years of experience as a product/user researcher in a tech environment, with strong hands-on expertise in qualitative methods: interviews, diary studies, think-aloud usability testing, and direct observation - Solid quantitative research skills: you're comfortable with survey design, sampling, crosstabs, and core statistical concepts - Sharp critical thinking: you quickly identify what research is worth doing, scope it efficiently, and deliver insights that are focused and actionable - A strategic mindset: you know how to partner with product stakeholders, communicate the value of research, and tie your findings to concrete business impact - Compelling communication skills: you turn complex findings into clear narratives that resonate with any audience - Experience mentoring junior researchers or non-researchers, with the ability to give clear, actionable feedback that helps others grow - You're close to AI. Either you've built AI products, or you follow the space closely and have a clear view on where to leverage and how LLM systems behave in production. - You care about healthcare. Alan's mission has to genuinely matter to you. For us this is essential, not a nice-to-have. - English fluency, written and spoken - (As a plus) Fluency in French, Spanish, or another European language For this role, we hire within the D-E level range. 🌍 HOW WE WORK - Based in (or within commuting distance of) one of our hubs (Paris, Bordeaux, Marseille, Brussels, Madrid, or Barcelona), with the ability to work onsite twice per week. 🎯 IMPORTANT NOTE: WE HIRE PEOPLE, NOT ROLES. If you're excited about this opportunity but don't check every box, we'd love to hear from you. Everyone, no matter how underrepresented, should feel free to apply, as it can only bring learnings or success. If you identify yourself as a woman: Did you know that research shows women often apply only when meeting 100% of requirements? Remember, this is just a guide, not a checklist. We'll be thrilled to receive your application! 🔖 Check out our About Alan https://alan.com/about and Career https://alan.com/careers pages, as well as our Medium https://medium.com/alan, blog https://blog.alan.com/ and Glassdoor page https://www.glassdoor.com/Overview/Working-at-Alan-EI_IE1696043.11,15.htm for more info. You want to know more about Alan? 🙌 Perks & Benefits https://alan.com/en/careers/a/salary-equity: Alaners are provided with a stimulating environment and perks ensuring they are happy, efficient and spend only high-quality time with co-workers. 🤘 A strong culture https://alan.com/en/about/a/leadership-principles: People joining Alan are often surprised and delighted by our innovative working method. We have a set of cultural values that guide our approach to work. #LI-DNP

Компания Marvell ищет стажера-исследователя с уровнем PhD для работы в области FPGA и прототипирования на кремнии. Кандидат должен быть зачислен в программу PhD, MS by Research или MTech by Research по направлениям компьютерных наук, компьютерной инженерии, электроники, электротехники, робототехники или смежным дисциплинам.

Amrita Vishwa Vidyapeetham at the Amritapuri Campus is seeking qualified individuals to join as Research Trainees. Candidates will be involved in research activities as part of their role. The position requires applicants to meet certain qualifications, though specific details about the tasks and requirements are provided on the official website.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: Large teams of agents are starting to solve problems no single agent can, from rewriting major codebases to formalizing landmark mathematics. Our team studies how these teams scale: what happens to performance, cost and coordination as the number of agents, the compute budget and the length of the task grow, and what has to change to keep getting returns from that scale. We build the platform and evaluations Anthropic uses to run and measure large agent teams, and other research teams build on them. This role lives at the boundary between research and engineering. It is a generalist role on a small team: you'll design and run large experiments, build the systems they run on, and get to the bottom of surprising results. We often need to go from a vague question to a running experiment quickly. Responsibilities: Design, run and interpret large-scale experiments on agent teams, reasoning rigorously about what the data does and doesn't show Investigate how performance and efficiency change as team size, compute and task horizon grow, and find the bottlenecks that limit them Build and scale the systems that run very large agent teams reliably, and debug the failures that only appear at scale Design evaluations for long-horizon problems, and keep their results trustworthy Build the tooling and metrics that let researchers see what a large agent team is doing and why Partner with research teams across Anthropic so they can run their own experiments on the platform, and communicate findings clearly You may be a good fit if you: Have significant software engineering, ML or research engineering experience Have owned something substantial end to end, such as a large system, an evaluation or benchmark, an agent product, or a research project Genuinely enjoy both research and engineering work Think quantitatively about complex systems, and think twice before trusting a number Can work from a vague question rather than a spec Are results-oriented, with a bias towards flexibility and impact Have clear written and verbal communication Care about the societal impacts of your work Strong candidates may also have: Experience building or operating large-scale distributed systems, such as schedulers, sandboxed code execution, or inference and RL infrastructure Built evaluations, benchmarks or harnesses for LLMs or agents Experience building complex agentic systems that use LLMs Experience with scaling laws or other large-scale empirical research A background in operations research, statistics, economics, physics, quantitative finance, or another field that models and optimizes complex systems Strong candidates need not have: Formal certifications or education credentials Academic research experience or publication history Prior experience with multi-agent systems or reinforcement learning Representative projects: Measure how performance scales with the number of agents on a hard problem, and explain where the curve bends and why Prepare our largest-ever agent run: find what breaks as team size and task length grow together, and fix it before launch Work out how to allocate a fixed compute budget across a team of agents to solve a problem fastest Build tooling that turns the activity of a large agent team into something a researcher can read in minutes Design a novel eval that distinguishes real gains in teamwork from artifacts of the evaluation setup The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: United States; Canada; United Kingdom; Germany; The Netherlands Workplace: Remote ClickHouse Labs is an applied research group that works closely with engineering teams to identify challenging problems in database systems and develop novel solutions. Our goal is to advance the state of the art and translate research ideas into real-world system improvements. ABOUT THE ROLE As a Research Scientist at ClickHouse Labs, you will work on high-impact problems at the intersection of database systems, distributed systems, AI, and systems software engineering while collaborating with experienced researchers and engineers. The role covers a broad range of problems across database systems research and engineering, including but not limited to query optimization, execution engines, distributed systems, consensus protocols, materialized views, indexing and data structures, benchmarking, workload analysis, and emerging agentic workloads. In this role, you will work on leading open-source database systems (e.g., ClickHouse, PostgreSQL). You will investigate performance and scalability bottlenecks in production-quality systems, develop new algorithms and system designs, and evaluate them under realistic workloads and hardware configurations. Projects may involve improving query planning and execution, reducing CPU and memory overhead, increasing throughput and concurrency, scaling across distributed deployments, or redesigning system components to leverage modern hardware better. You will work closely with engineers to turn successful ideas into robust implementations that can be deployed and maintained in widely used open-source systems. Researchers are encouraged to publish their work, contribute to open-source projects, participate in leading research conferences, and pursue ambitious projects with strong engineering and research support. RESPONSIBILITIES - Conduct applied research aimed at advancing the performance, scalability, reliability, and functionality of open-source database management systems, including ClickHouse and PostgreSQL. - Design and evaluate new algorithms, data structures, and system architectures for areas such as query optimization, indexing, storage management, query execution, and distributed data management. - Develop high-quality research prototypes and production-grade implementations, and work with engineering teams to integrate successful techniques into open-source and production systems. - Collaborate closely with database engine, infrastructure, and data-plane engineers to identify high-impact research problems and translate research results into practical system improvements. - Analyze large-scale database workloads, performance traces, benchmarks, and production telemetry to identify bottlenecks and optimization opportunities. - Design rigorous experiments and benchmarks to evaluate new techniques across realistic workloads, hardware configurations, and deployment environments. - Communicate research results through technical reports, open-source contributions, internal presentations, and publications at leading database and systems venues (e.g., SIGMOD, VLDB, CIDR). - Contribute to the broader technical direction of ClickHouse Labs by identifying emerging research opportunities and helping shape longer-term research projects. QUALIFICATIONS MINIMUM QUALIFICATIONS - Masters/Ph.D. in Computer Science, Data Science, or a related field, with research experience in databases, distributed systems, systems software, or machine learning systems. - Strong publication record in leading peer-reviewed research venues such as SIGMOD, VLDB, SOSP, OSDI, NSDI, or NeurIPS, with work relevant to databases or systems. - Strong programming and systems-development background, including experience working with database internals or other large systems codebases such as PostgreSQL, MySQL, ClickHouse, or comparable modern DBMSs. - Proficiency in systems programming using C, C++, Rust, Zig, or a comparable low-level programming language. - Strong analytical, experimental, problem-solving, and technical communication skills. PREFERRED QUALIFICATIONS - Experience developing or operating database systems in cloud environments such as AWS, Google Cloud Platform, or Microsoft Azure. - Familiarity with large language models, reinforcement learning, learned optimization, or other techniques at the intersection of machine learning and systems. - Experience contributing to large open-source systems projects, particularly database engines, distributed systems, compilers, or storage systems. BONUS QUALIFICATIONS - Familiarity with modern systems-development and verification tooling, including formal specification or model-checking frameworks such as TLA+/PlusCal, Alloy, or Lean, as well as relevant development tools and languages such as LLVM, eBPF, Python, Go, or advanced profiling and debugging tools (e.g., perf, sanitizers, or tracing frameworks). - Proven track record in optimizing database systems via hardware acceleration (e.g., GPU, FPGA, CXL), with a focus on designing methods for offloading for query execution, storage layers, and data-intensive primitives using frameworks like CUDA, SYCL, ROCm, or specialized FPGA development flows. PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: India Workplace: Remote PRIVATE EQUITY AI RESEARCHER (IC Decks, Board Materials) Full time | Remote — India ABOUT US Aptura is a London-based company working on understanding how AI is changing professional work. We look closely at how finance and advisory professionals actually work, and where AI helps or falls short. The company was founded by people with backgrounds at Lazard, McKinsey and Partners Group. ROLE DESCRIPTION We are looking for Subject Matter Experts from private equity, private credit or corporate development who build IC papers, board materials and portfolio updates. You know which slide the committee turns to first, and why AI rarely gets it right. You have used AI tools on your own work and been frustrated by the mistakes they make, or you simply want to find out how good they really are. You will turn that experience into realistic PowerPoint tasks that test how well AI do the deck work of an investment associate. RESPONSIBILITIES INCLUDE - Writing realistic PowerPoint tasks drawn from your own investment and portfolio work: building decks from source documents, filling corporate templates, rolling decks forward and making precise edits - Working through each task yourself so there is a clear, correct answer - Writing a yes-or-no checklist precise enough that an AI grader can mark any attempt against it NECESSARY SKILLS INCLUDE - 2+ years in private equity, growth equity, private credit or corporate development - Deep hands-on PowerPoint: native charts, tables and corporate templates - Ability to define what a correct deck looks like precisely enough for someone else to grade against it - Clear writing. Tasks must be written by you, not by AI tools - Attention to detail, and willingness to learn concepts in AI and data HOW IT WORKS 1. Apply with your details and CV. After applying, verify your email and choose an available 30-minute group walkthrough call. You can book immediately; there is no application-approval step before booking. 2. Attend the walkthrough and enter the code shared by the host at the end of the call to unlock your task workspace. 3. Create one original task from your own work in about 45 minutes. Submit the brief, the actual input files needed to complete it, a written expected result and at least five binary rubric checks, each with one skill tag. Input-file uploads are compulsory. 4. Write the brief and rubric yourself, without AI drafting, rewriting or polishing. Input materials must also be human-authored. Use only materials you are authorised to share, with confidential employer or client information removed. 5. Submit through your account for automated screening and team review. Follow any request for revisions in your account. Completing onboarding does not guarantee a job offer; selection remains subject to review. LOCATION Remote — India

Задачи: — Поиск и сбор релевантной информации по заданиям команды: компании, конкуренты, лиды, поставщики, партнёры, форумы, отзывы, объявления и другие источники. — Поиск кандидатов, поставщиков и партнёров через LinkedIn, job boards, доски объявлений, профильные форумы и специализированные площадки. — Поиск информации на тематических форумах, в Telegram, Discord и других нишевых сообществах. — Проведение первичного outreach: установление контакта, ведение диалога и получение необходимой информации. — Создание и ведение рабочих аккаунтов на необходимых площадках под конкретные задачи. — Использование инструментов массового поиска, фильтрации, парсинга и базовой автоматизации. — Работа с AdsPower и аналогичными инструментами при необходимости. — Работа с proxy и инструментами для доступа к региональным ресурсам в рамках законодательства и внутренних правил. — Проверка и верификация найденной информации по нескольким источникам. — Работа с большими массивами информации: из большого количества источников выделять 3–7 действительно релевантных и обосновывать выбор. — Подготовка структурированных отчётов: ссылка → краткая выжимка → приоритет → рекомендация. — Передача команде найденных контактов, информации и рекомендаций по дальнейшим действиям. Требования: — Опыт в internet research / sourcing от 1–2 лет. — Опыт OSINT будет большим преимуществом, но не является обязательным. — Сильные навыки поиска информации в интернете, в том числе через нестандартные и нишевые источники. — Уверенная работа с LinkedIn, job boards, досками объявлений, форумами и другими профильными площадками. — Опыт поиска информации через Telegram, Discord и тематические сообщества. — Умение создавать и вести рабочие аккаунты на различных платформах. — Базовое владение инструментами парсинга и автоматизации. — Опыт или понимание работы с AdsPower и аналогичными инструментами. — Понимание принципов работы proxy. — Умение проверять достоверность и актуальность найденной информации. — Сильные аналитические навыки: способность из большого массива данных выделять действительно ценную информацию. — Умение самостоятельно устанавливать контакт, вести диалог и получать необходимую информацию. — Английский — Intermediate+ для работы с англоязычными источниками и ведения переписки. — Ответственность, самостоятельность, внимательность к деталям и соблюдение конфиденциальности. — Гибкость и хорошие коммуникативные навыки.

Location: Boston, MA Workplace: OnSite At WHOOP, we’re on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies, behaviors, and daily lives. WHOOP is hiring an Associate Director of Design Research to lead and scale the Design Research practice at WHOOP. This role will oversee Design Research, shaping how user feedback and experiences inform product innovation from early-stage insights to pre-launch validation studies to post-launch feedback. As a people-first leader, you will balance strategic direction, team development, and leadership evangalism—ensuring research rigor, creativity, and impact across the product lifecycle. RESPONSIBILITIES: - Provide strategic leadership for the design research team, ensuring alignment with key stakeholders and organizational priorities. - Evangelize the importance of user insights and the role of design research in the product and hardware development lifecycle to WHOOP senior leadership. - Scale research impact, working closely with cross-functional leaders to identify opportunities for research and set expectations for mixed-methods research, ensuring research is positioned as a critical input to decision-making. - Partner closely with senior team members to review research needs, assess tradeoffs, and guide prioritization and research direction. - Manage, coach, and develop a team of design researchers, fostering strong research craft, clear communication, and professional growth. - Own relationships with external research vendors, including scoping projects, defining success criteria, and ensuring high-quality execution. - Build a strong, cross-functional “voice of the member” for product decision-making in partnership with Consumer Insights, Analytics, and Membership Services. QUALIFICATIONS: - Bachelor’s degree in a relevant field such as human factors, design research, user experience research, design anthropology, psychology, or a related discipline. - 5+ years of experience conducting user research for physical products, ideally within hardware, health, or consumer product environments. - 5+ years of people management experience, including coaching, feedback, and performance development. - Strong mixed-methods research background, with demonstrated application of qualitative and quantitative approaches to real-world products. - Experience working within or alongside hardware development lifecycles (not software-only). - Experience managing or partnering with external research vendors, including project scoping and execution. - Ability to manage multiple workstreams, navigate ambiguity, and influence without direct authority across cross-functional teams. - Excellent written, verbal, and presentation skills, with the ability to communicate complex insights to executive audiences. - Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions. *This role is based out of our Boston, MA headquarters and requires work onsite Monday-Friday. Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success. The U.S. base salary range for this full-time position is $140,000 - $180,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

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

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

Location: United States About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . The Role Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for the world’s leading AI labs and enterprises. We create RL environments to evaluate and improve our customers' models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, Customer Experience. The environments vary depending on the model capability being evaluated / improved, a few examples of environment types are listed here: Environments for Software Engineering / coding agents UI-Environments for Computer-Use/Browser-Use agents MCP-based Environments for general function-calling agents across various enterprise and consumer applications We are seeking Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. What You’ll Do 1. Conduct Research on Frontier AI Systems Investigate the capabilities, limitations, and training methods of frontier AI systems. Formulate research questions that can inform Turing’s products, platforms, and technical strategy. Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. Stay current with advances in machine learning and identify opportunities for meaningful technical contribution. 2. Build and Evaluate Research Systems Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks. Train, test, and evaluate models using modern AI and machine learning tools. Analyze results carefully and draw clear, evidence-based conclusions. Establish sound practices for experimental rigor, data quality, reproducibility, and interpretation. Iterate quickly from early hypothesis through validated technical insight. 3. Translate Research into Practical Impact Collaborate closely with Research, Engineering, Product, and Operations teams. Translate research findings into improvements for Turing’s products, platforms, and AI capabilities. Help identify which ideas are ready to move from exploration into scalable, real-world applications. Communicate technical findings clearly to both specialized and cross-functional audiences. 4. Contribute to the Research Community Share findings through technical reports, publications, open-source work, workshops, or conference participation where appropriate. Contribute to Turing’s research culture through technical discussions, peer review, mentorship, and collaboration. Represent Turing thoughtfully within the broader AI research community. What We’re Looking For Research background: PhD or Master’s degree in artificial intelligence, machine learning, computer science, or a closely related technical field; exceptional equivalent research experience will also be considered. Technical depth: Strong foundation in machine learning and practical experience designing experiments, training or evaluating models, and working with modern AI tooling. Relevant expertise: Demonstrated research experience in synthetic or agentic data generation, reinforcement learning or post-training, AI understanding, evaluation, or benchmarks. Research engineering ability: Strong programming skills and the ability to implement, test, and iterate quickly in a research environment. Scientific judgment: Sound judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making. Communication and collaboration: Clear written and verbal communication skills, intellectual curiosity, and the ability to work effectively across research and engineering teams. A note from our CTO, Ece Kamar Some of the most important questions in AI can't be answered from inside a single lab: how to evaluate frontier models, how data and RL truly drive capability, and what happens when AI meets the real world. At Turing, we work directly with frontier labs, the academic community, and enterprises deploying AI at scale. That creates a feedback loop where deployment shapes our research and our research shapes the field, and we publish our findings, datasets, and benchmarks openly. Join our talented team at Turing to push the frontier of AI with rigorous science that matters. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training and RL environment design. Build datasets and environments that directly improve the capabilities of advanced AI systems. Help advance coding agents’ ability to understand, plan, and execute complex software-engineering tasks. Apply frontier AI innovations to high-value enterprise workflows. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. Compensation: $250,000 to $350,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: United States About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . The Role Turing is seeking exceptional Research Scientists to join our research organization and develop new ways to evaluate, train, and improve frontier AI systems. This is a research-first role focused on problems where the right benchmark, dataset, or methodology often does not yet exist. You will identify important gaps in the literature, propose ambitious new research directions, and take projects from initial hypothesis through experimentation, benchmark construction, and publication. Our research is deliberately focused on frontier evaluation, synthetic data, hallucination and reliability, and agentic science . We are looking for scientists who can recognize important problems early, formulate them precisely, and design rigorous research programs to answer them. What You'll Do Frontier benchmarks and evaluation Identify high-impact gaps in existing benchmark and evaluation literature. Design novel benchmarks in and across STEM fields and on general model functionality. Develop evaluations for emerging model capabilities that are poorly captured by traditional static benchmarks. Design rigorous task-generation, grading, contamination-control, difficulty-calibration, and validation methodologies. Build benchmarks that can become both valuable research contributions and meaningful standards for evaluating frontier models. Synthetic data and post-training Develop methods for generating high-quality synthetic STEM training data. Study how task selection, difficulty, diversity, verification, filtering, and data quality affect downstream performance. Explore methods for generating useful training signal in domains where expert human data is scarce or expensive. Design experiments that determine when synthetic data genuinely improves capabilities rather than simply increasing training volume. Hallucination, reliability, and verification Study hallucination, uncertainty, calibration, and epistemic failure in technical domains. Develop evaluations and methods for improving factual reliability, self-correction, verification, citation, and appropriate abstention. Investigate when models should reason internally, invoke tools, seek external evidence, or recognize that they do not know. Agentic science Research AI systems capable of performing extended scientific and technical work. Develop workflows involving literature search, coding, simulation, tool use, experimentation, verification, and iterative reasoning. Evaluate long-horizon scientific agents and identify the bottlenecks preventing them from reliably performing real research. Explore new approaches to human-AI and multi-agent scientific collaboration. New research directions The areas above are our core focus, not an exhaustive list. Researchers will also have significant latitude to propose new programs in areas such as reasoning, model evaluation, AI-for-science, data generation, and emerging capabilities. What We’re Looking For PhD or equivalent research experience in machine learning, computer science, mathematics, physics, chemistry, biology, engineering, statistics, or another highly technical field . Demonstrated ability to formulate and execute original research. Strong understanding of modern LLMs and the frontier AI research landscape. Excellent experimental design, quantitative reasoning, and scientific judgment. Ability to rapidly understand unfamiliar technical literature and develop expertise in new areas. Strong Python skills and the ability to independently build research prototypes and evaluation pipelines. Excellent technical writing and communication. Comfort working in a fast-moving environment where the research agenda evolves with the frontier. A strong publication record is valuable, but we care most about whether you can identify important questions, design rigorous ways to answer them, and execute quickly enough for the results to matter . A note from our CTO, Ece Kamar Some of the most important questions in AI can't be answered from inside a single lab: how to evaluate frontier models, how data and RL truly drive capability, and what happens when AI meets the real world. At Turing, we work directly with frontier labs, the academic community, and enterprises deploying AI at scale. That creates a feedback loop where deployment shapes our research and our research shapes the field, and we publish our findings, datasets, and benchmarks openly. Join our talented team at Turing to push the frontier of AI with rigorous science that matters. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training and RL environment design. Build datasets and environments that directly improve the capabilities of advanced AI systems. Help advance coding agents’ ability to understand, plan, and execute complex software-engineering tasks. Apply frontier AI innovations to high-value enterprise workflows. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. Compensation: $250,000 to $400,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: United States About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . The Role Turing is seeking exceptional Research Scientists to join our STEM research organization and develop new ways to evaluate, train, and improve frontier AI systems. This is a research-first role focused on problems where the right benchmark, dataset, or methodology often does not yet exist. You will identify important gaps in the literature, propose ambitious new research directions, and take projects from initial hypothesis through experimentation, benchmark construction, and publication. Our research is deliberately focused on frontier STEM evaluation, synthetic data, hallucination and reliability, and agentic science . We are looking for scientists who can recognize important problems early, formulate them precisely, and design rigorous research programs to answer them. What You'll Do Frontier benchmarks and evaluation Identify high-impact gaps in existing benchmark and evaluation literature. Design novel benchmarks in and across STEM fields and on general model functionality. Develop evaluations for emerging model capabilities that are poorly captured by traditional static benchmarks. Design rigorous task-generation, grading, contamination-control, difficulty-calibration, and validation methodologies. Build benchmarks that can become both valuable research contributions and meaningful standards for evaluating frontier models. Synthetic data and post-training Develop methods for generating high-quality synthetic STEM training data. Study how task selection, difficulty, diversity, verification, filtering, and data quality affect downstream performance. Explore methods for generating useful training signal in domains where expert human data is scarce or expensive. Design experiments that determine when synthetic data genuinely improves capabilities rather than simply increasing training volume. Hallucination, reliability, and verification Study hallucination, uncertainty, calibration, and epistemic failure in technical domains. Develop evaluations and methods for improving factual reliability, self-correction, verification, citation, and appropriate abstention. Investigate when models should reason internally, invoke tools, seek external evidence, or recognize that they do not know. Agentic science Research AI systems capable of performing extended scientific and technical work. Develop workflows involving literature search, coding, simulation, tool use, experimentation, verification, and iterative reasoning. Evaluate long-horizon scientific agents and identify the bottlenecks preventing them from reliably performing real research. Explore new approaches to human-AI and multi-agent scientific collaboration. New research directions The areas above are our core focus, not an exhaustive list. Researchers will also have significant latitude to propose new programs in areas such as reasoning, model evaluation, AI-for-science, data generation, and emerging capabilities. What We’re Looking For PhD or equivalent research experience in machine learning, computer science, mathematics, physics, chemistry, biology, engineering, statistics, or another highly technical field . Demonstrated ability to formulate and execute original research. Strong understanding of modern LLMs and the frontier AI research landscape. Excellent experimental design, quantitative reasoning, and scientific judgment. Ability to rapidly understand unfamiliar technical literature and develop expertise in new areas. Strong Python skills and the ability to independently build research prototypes and evaluation pipelines. Excellent technical writing and communication. Comfort working in a fast-moving environment where the research agenda evolves with the frontier. A strong publication record is valuable, but we care most about whether you can identify important questions, design rigorous ways to answer them, and execute quickly enough for the results to matter . A note from our CTO, Ece Kamar Some of the most important questions in AI can't be answered from inside a single lab: how to evaluate frontier models, how data and RL truly drive capability, and what happens when AI meets the real world. At Turing, we work directly with frontier labs, the academic community, and enterprises deploying AI at scale. That creates a feedback loop where deployment shapes our research and our research shapes the field, and we publish our findings, datasets, and benchmarks openly. Join our talented team at Turing to push the frontier of AI with rigorous science that matters. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training and RL environment design. Build datasets and environments that directly improve the capabilities of advanced AI systems. Help advance coding agents’ ability to understand, plan, and execute complex software-engineering tasks. Apply frontier AI innovations to high-value enterprise workflows. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. Compensation: $250,000 to $350,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .