Вакансии

Задачи: — Планирование и проведение UX-исследований, включая глубинные интервью, опросы и юзабилити-тестирования; — Самостоятельная организация исследований: поиск респондентов, подготовка сценариев и проведение интервью; — Анализ результатов, выявление инсайтов, проблем и потребностей различных сегментов пользователей; — Документирование результатов и презентация выводов командам; — Оценка влияния продуктовых изменений на пользовательский опыт; — Изучение конкурентов, рыночных трендов и лучших UX/CX-практик. Требования: — Опыт проведения UX-исследований, особенно глубинных интервью; — Понимание качественных и количественных методов исследования; — Сильные аналитические и коммуникационные навыки; — Умение выявлять реальные проблемы пользователей и отличать факты от гипотез; — Английский язык на уровне, достаточном для проведения интервью; — Опыт работы с международными рынками; — Знание Figma; — Базовое понимание SQL будет преимуществом (аналитика в ClickHouse). Условия: — Полностью удалённая работа; — Работа в сильной продуктовой команде с быстрым циклом принятия решений; — Ориентация на результат; — Возможность экспериментов и реальное влияние на продукт.

Location: New York Who We Are: Galaxy Digital Inc. (Nasdaq: GLXY) is a global leader in digital assets and data center infrastructure, growing the economy that runs on code. Galaxy delivers the onchain infrastructure that connects institutions to digital assets, including trading, advisory, asset management, staking, self-custody, and tokenization. Galaxy also develops and operates data center infrastructure to power AI and HPC workloads. Anchored by its Helios campus in Texas, Galaxy is building a multi-gigawatt pipeline of more than 5.7 GW of potential capacity, positioning it among the largest and fastest-growing data center developers in North America. The Company is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia. Additional information about Galaxy's businesses and products is available on www.galaxy.com . What We Value: We are a diverse team of free thinkers, and fast movers united to help investors and creators energize the global economy. We are looking for individuals who thrive in a culture of builders and overachievers and embrace high performance, transparent feedback, and a mission-first approach. Our culture shapes our way of working and gets us where we want to be. Seek Excellence. Be Selective To Be Effective. Be Highly Aligned, Loosely Coupled. Disagree Transparently. Encourage Independent Decision-Making. Build Dream Teams. About the Galaxy Summer Internship Program The Galaxy NYC Summer Internship Program is an immersive, nine-week experience taking place on-site in our New York HQ office. During the nine weeks, you will gain hands-on, practical work experience on our Research team, working on real products and problems alongside the people building them. In addition to learning on the job, Galaxy interns participate in professional development programming, social events, and networking opportunities with senior leaders. Program Dates : June 7th – August 6th, 2027 What You'll Do: Assist business units with Research work product Learn how to and produce reports about cryptocurrency networks and markets Support the growth of Galaxy’s distribution platforms (newsletter, podcasts, Research Portal) Gain exposure to crypto technologies, markets, investment vehicles Support Galaxy Research’s efforts in Washington as policy advisors What We're Looking For: Excellent verbal and written communication skills Exceptional analytical, organizational, and creative skills Deep interest in and existing knowledge of cryptocurrency networks and markets Skills in any of the following: data analysis, financial analysis and modeling, markets and trading, software engineering, computer science, cryptography, network analysis, cybersecurity research Eligibility Requirements: Undergraduate or master’s students graduating between December 2027 and June 2028 Eligible master’s students must have fewer than two years of relevant, full-time work experience Students enrolled in PhD or JD programs are not eligible to apply Here are some of the industry-leading benefits of interning at Galaxy: Opportunities to learn about the Digital Asset and Data Center industry Free daily snacks and weekly lunches Smart, entrepreneurial and fun colleagues Employee Resource Groups *Benefits may vary based on location. Interns are classified as non-exempt employees and will be paid a rate of $55/hr. Galaxy respects diversity and seeks to provide equal employment opportunities to all employees and job applicants for employment without regard to actual or perceived age, race, color, creed, religion, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression (including transgender status), sexual orientation, marital or partnership or caregiver status, ancestry, national origin, citizenship status, disability, military or veteran status, protected medical condition as defined by applicable state or local law, genetic information or predisposing genetic characteristic, or other characteristic protected by applicable federal, state, or local laws and ordinances. We will endeavor to make a reasonable accommodation to the known limitations of a qualified applicant with a disability unless the accommodation would impose an undue hardship on the operation of our business. If you believe you require such assistance to complete the application process or to participate in an interview, please contact careers@galaxy.com.

The Quantum Research Scientist will advance quantum information science and optical quantum systems, leveraging expertise in continuous-variable photonics and theoretical algorithm discovery to translate complex physical phenomena into experimental prototypes and publishable research. Responsibilities include but are not limited to:

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

Location: Москва Департамент автономных решений объединяет направления робототехники и аэрологистики Сбера. Команда развивает проекты в области Physical AI, автономного вождения и других AI-решений, повышая масштаб, надёжность и эффективность автономных технологий. Мы ищем руководителя, который выстроит системную работу с академическим сообществом и исследовательскими программами: от формирования потребностей внутренних команд до запуска совместных проектов с вузами и научными центрами. Обязанности * формирование и управление портфелем исследовательских и академических программ * развитие стратегических партнёрств с вузами и научно-исследовательскими центрами * формирование карты исследовательских потребностей в робототехнике, беспилотных технологиях и Physical AI * координация исследовательских инициатив: от выявления потребности до запуска сотрудничества * сопоставление академических предложений с задачами и приоритетами внутренних команд * выстраивание единой системы взаимодействия с академическими партнёрами и исследовательскими командами. Требования * опыт управления исследовательскими, научно-технологическими или академическими программами * практический опыт развития партнёрств с вузами, научными центрами или R&D-организациями * опыт формирования исследовательской повестки и структурирования научно-технологических потребностей * опыт управления комплексными проектами и координации межфункциональных команд * опыт сопровождения проектов от формирования концепции до запуска и реализации * способность самостоятельно выстраивать процессы и отвечать за результат направления. Будет преимуществом: * опыт в робототехнике, беспилотных системах, Physical AI/AI * опыт управления портфелем исследовательских инициатив * опыт реализации совместных научно-технологических проектов с вузами. Условия * работа из офиса по адресу г Москва, пр-кт Кутузовский, 32 к3  * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Isomorphic Labs is looking for a Senior Research Investigator to develop computational models and methods for biologics discovery and therapeutic design.

Isomorphic Labs is looking for a Senior Research Investigator to lead pharmacology strategy and advance biologics candidates through drug discovery.

Location: San Francisco, CA 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 Anthropic's Life Sciences team is building a research group focused on biological discoveries by combining AI with hands-on biological research. We're seeking a research scientist with deep expertise in antibody process development and manufacturing to join the team. Our goal is to speed up progress in the life sciences by an order of magnitude, and this role puts that mission into practice. You'll be an expert in making antibodies, with hands-on experience expressing, purifying, characterizing, and formulating them, from small screening batches to material for IND-enabling studies. Above all, you'll close the loop between AI-generated hypotheses and experimental data to share with the community. Working alongside AI researchers and engineers, you'll build and run the workflows that turn AI-designed sequences into well-characterized protein, and pressure-test AI predictions of expression, stability, and manufacturability against real data. This role is fully on-site in the San Francisco Bay Area. Key responsibilities Develop and run expression and purification processes for antibodies and other recombinant proteins end to end, including transient and stable expression in mammalian cells (HEK293, CHO), affinity capture (Protein A, IMAC), polishing chromatography, buffer exchange, and formulation Characterize what we make with the right analytical panel, for example SEC, CE-SDS, icIEF, LC-MS (intact mass, peptide mapping, glycans), DLS, thermal stability, endotoxin, and binding kinetics (SPR, BLI) Build the laboratory for this work, including selecting, installing, and qualifying equipment and setting up workflows that scale from plate-based production of hundreds of designs to gram quantities of a lead Evaluate AI-designed antibodies for manufacturability (titer, aggregation, stability under stress, viscosity, chemical liabilities), drive them to experimental readout, and feed results back to research teams Plan the chemistry, manufacturing, and controls (CMC) path toward IND-enabling studies, from cell line development and scale-up to analytical methods and stability, and coordinate technology transfer and manufacturing with external contract manufacturers Ensure experimental data across programs is high quality and well documented, including batch records, methods, raw data, and failure modes Communicate findings clearly to biology, AI research, and life sciences audiences Minimum qualifications PhD in biochemical engineering, chemical engineering, biochemistry, or a related field Demonstrated experience in process development and manufacturing of antibodies or other recombinant proteins, including material supplied for IND-enabling or clinical studies, with recent, sustained hands-on laboratory work Comfort navigating ambiguity and defining problems in a rapidly evolving research environment Ability to work independently while collaborating effectively across cross-functional teams, with strong written and verbal communication skills Preferred qualifications 5+ years of biologics process development experience beyond the PhD Depth in both upstream (cell line development, bioreactors) and downstream (chromatography, filtration) development, with working knowledge of analytical and formulation development Experience setting up a protein production or process development laboratory, including laboratory automation and high-throughput, plate-based expression and purification Experience directing technology transfer and GMP manufacturing at contract development and manufacturing organizations, with contributions to the CMC sections of an IND Statistics or coding skills, for example design of experiments or Python for data analysis and automation Experience using AI or ML tools in the life sciences Publications and/or patents demonstrating scientific impact 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: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA 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 Anthropic's Life Sciences team is building a research group focused on biological discoveries by combining AI with hands-on biological research. We're seeking a research scientist with deep expertise in therapeutic antibodies to join the team. Our goal is to speed up progress in the life sciences by an order of magnitude, and this role puts that mission into practice. You'll be an expert in antibody design and engineering who has taken antibodies through the whole process, from target selection and lead optimization to candidate selection and IND-enabling studies. Above all, you'll close the loop between AI-generated hypotheses and experimental data to share with the community. Working alongside AI researchers and engineers, you'll drive antibody programs end to end and pressure-test AI-designed antibodies against the bar a real drug candidate has to clear. This role is fully on-site in the San Francisco Bay Area. Key responsibilities Design and engineer therapeutic antibodies and oversee programs end to end, including target and epitope selection, choice of format (IgG, Fab, scFv, VHH, bispecific), humanization, affinity maturation, Fc engineering, and candidate selection Define the screening cascade for each program, from binding kinetics (SPR, BLI), epitope binning, and species cross-reactivity to cell-based functional assays and developability (expression, aggregation, polyreactivity, stability, viscosity, immunogenicity risk) Plan the path from lead to IND-enabling studies, including in vivo pharmacology, pharmacokinetics, toxicology, and the handoff to process development and manufacturing Coordinate antibody production, characterization, and in vitro and in vivo studies with external contract research organizations and academic partners Evaluate AI-designed antibodies, drive them to experimental readout, and feed results back to research teams Ensure experimental data across programs is high quality and well documented, including sequences, protocols, raw data, and failure modes Communicate findings clearly to biology, AI research, and life sciences audiences Minimum qualifications PhD in biochemistry, protein engineering, immunology, molecular biology, or a related field Demonstrated experience in therapeutic antibody discovery and engineering, including at least one antibody you helped take from discovery through candidate selection and IND-enabling studies Working knowledge of what an antibody IND requires across pharmacology, pharmacokinetics, toxicology, and chemistry, manufacturing, and controls (CMC) Comfort navigating ambiguity and defining problems in a rapidly evolving research environment Ability to work independently while collaborating effectively across cross-functional teams, with strong written and verbal communication skills Preferred qualifications 5+ years of therapeutic antibody experience beyond the PhD Track record of advancing more than one antibody program into IND-enabling studies or the clinic, with contributions to pre-IND or IND documents Hands-on experience with antibody expression, purification, and biophysical characterization Experience directing antibody production, assays, and in vivo studies at contract research organizations Structural biology, computational protein design, or coding skills, for example Python for sequence and assay data analysis or structure prediction and protein design tools Experience using AI or ML tools in the life sciences Publications and/or patents demonstrating scientific impact 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: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: London, United Kingdom Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. About the Team DoorDash’s mission is to grow and empower local economies. By building intelligent, last-mile delivery technology for local cities, DoorDash connects people with the local businesses they care about — helping grow businesses and the communities that support those businesses. At DoorDash, there are three audiences that are at the core of every decision we make - our Consumers, Merchants, and Couriers. The Research team has a direct link to uncover the unmet needs and pain points of each of these audiences. We bring their voices into the business in order to help set the strategic vision for all of DoorDash’s current and future products. About the Role We’re looking for a Principal Researcher to be a strategic research leader for EMEA, shaping what DoorDash builds next. You’ll combine deep expertise in qualitative and quantitative methods to find the unmet needs, behavioral shifts, and market openings that point to new products and new growth. You’ll work as a peer to senior product, design, engineering, data science, and business leaders, and your work will directly inform roadmaps, investment decisions, and company-level strategy. This role is built for a seasoned researcher who is equally comfortable in a living room interview, a survey dataset, and a leadership review, and who uses AI as a daily tool to move faster and see further, without giving up the judgment that makes research trustworthy. You’ll also raise the bar for the wider research practice by mentoring researchers, sharing methods, and helping the team define what great looks like in an AI-enabled era. What You’ll Be Doing Shape Product Strategy: Translate deep understanding of Consumers, Merchants, and Couriers into a clear point of view on where DoorDash should play and win. You’ll frame the highest-stakes questions, bring evidence to roadmap and investment debates, and influence decisions at the director and executive level. Detect New Opportunities: Proactively identify emerging needs, behavior changes, and white space that point to new products, new verticals, and new growth levers. You’ll size and validate opportunities with a mix of foundational discovery, market and competitive context, and behavioral data, and turn them into concepts teams can act on. Lead Mixed-Methods Research: Design and run rigorous research end to end, choosing the right method for the question: ethnography, in-depth interviews, diary studies, and usability testing alongside surveys, conjoint and MaxDiff, segmentation, experiment design, and behavioral and log analysis. You’ll triangulate across sources so the “what,” the “how much,” and the “why” tell one coherent story. Partner with Data Science and Experimentation: Work closely with data science and analytics to connect qualitative insight to A/B test design, metrics, and product outcomes, and to explain the “why” behind results. You’ll help teams learn from what worked, what didn’t, and what to test next. Apply AI to the Research Craft: Use AI tools and LLMs in your daily workflow for synthesis, analysis, survey and discussion guide design, and scaling qualitative depth, and design human-in-the-loop checks that catch confident but wrong outputs. You’ll help the team identify where AI accelerates research and where it should not be trusted, and contribute to shared prompts, workflows, and standards. You’ll also study how people experience AI-powered features across DoorDash’s products. Influence and Communicate: Tell compelling, decision-ready stories that move partners from insight to action. You’ll adapt depth and format to the moment, from a fast directional read that unblocks a team this week to a foundational body of work that anchors a multi-year strategy, and you’ll follow through to see that findings change what gets built. Lead Through Others: Serve as a thought partner and mentor to researchers across levels, review and elevate research quality, and help partners run good research on their own where that makes sense. You’ll help set the team’s research agenda, methods, and standards, and contribute to hiring and growing the team. Operate Across Brands and Regions: Bring a global lens to your work, partnering across brands, markets, and cultures and adapting approaches to local context so that insights scale beyond a single market. What We’re Looking For 10+ years of experience in user, market, or product research at a technology company (or equivalent depth), with a track record of leading ambiguous, high-visibility work at staff level or above Demonstrated impact on product strategy: examples where your research changed a roadmap, unlocked a new product or line of business, or redirected significant investment Proven ability to detect and shape new product or growth opportunities, from early signal through validated concept Expert command of both qualitative and quantitative methods, including interviews, ethnography, and usability testing as well as survey design, statistical analysis, and experimentation. Working knowledge of SQL, R, or Python for pulling and analyzing your own data is a plus Hands-on experience using AI and LLMs in research (for example, synthesis, analysis, prototyping, or scaling qualitative work), with sound instincts about where they help and where they mislead. Experience researching AI-powered products is a plus Experience in consumer, two-sided or multi-sided marketplace, logistics, commerce, or local services contexts is a plus Exceptional storytelling and executive presence, with the ability to influence senior stakeholders without authority and build trust across product, design, engineering, data science, and business teams A bias for speed and pragmatism: comfortable delivering directional insight quickly while knowing when a decision calls for deeper rigor Experience mentoring or coaching researchers and raising the quality of a research practice Advanced degree in HCI, Psychology, Sociology, Anthropology, Economics, Statistics, Survey Methodology, or a related field preferred, or equivalent practical experience Why Join Us? At Deliveroo, you’ll do work that matters, solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠 Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎 A culture built for builders High standards, collaboration, flexible working and continuous learning. ​​💰 Share in the success you help create Competitive salary and equity options, so you’re rewarded for the impact you make. ➡️ Want a deeper look at how we build? Check out our Tech Blog . Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness .

Location: London, UK 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 The Anthropic Residency is our paid, fixed-term research program, with placements lasting between six weeks and six months. We are looking for people who have led ambitious work in a variety of technical fields and want to transition to full-time work focused on making sure AI systems are safe and beneficial for all of humanity. If you are a professor in a quantitative discipline, a technical founder or a staff-level engineer and want to transition to work on transformative AI, we want to hear from you. Background in machine learning is not required. What to expect A concrete, scoped project matched to your background, with direct mentorship from Anthropic researchers Access to Claude models and GPU compute Connection to the broader AI safety and security research community Interview process The interview process will include an initial application, recruiter screen, technical assessment, research discussion and a reference check. Applications for this round close on November 22, 2026 (11:59 PM PT). We expect to make offers in January 2027. You may be a good fit if you Are motivated by making sure AI is safe and beneficial for society as a whole Are excited to transition into working on empirical AI research full-time Have led ambitious work in a variety of technical fields (professor in a quantitative discipline, a technical founder or a staff-level engineer) Thrive in fast-paced, collaborative environments Can implement ideas quickly and communicate clearly Strong candidates may also Have experience authoring research papers in machine learning, NLP, or AI safety Have experience with LLMs, reinforcement learning or Kubernetes clusters and complex shared codebases Mentors and research areas Potential Anthropic mentors include: Sara Price : leads the Alignment Training team; background in data science Ethan Perez : leads the Alignment Science team; background in machine learning Evan Hubinger : leads the Alignment Stress-Testing team; formerly at The Machine Intelligence Research Institute (MIRI) Samuel Marks : leads the Scalable Oversight team; background in mathematics Elana Simon : researches the interpretability of language models and biological models; background in biomedical informatics Belinda Li : researches how language models represent the world, users, and themselves; background in natural language processing (PhD, MIT) Jack Lindsey : leads the Model Psychology team; background in theoretical neuroscience Nicholas Carlini : researches adversarial machine learning and AI security; previously at DeepMind and Google Brain Jascha Sohl-Dickstein : works at the intersection of safety and pretraining; background in physics and neuroscience, formerly Principal Scientist at Google Brain Residents will work on empirical research questions in collaboration with Anthropic's research teams. Areas we are particularly interested in include: AI safety & alignment Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains. Adversarial Robustness and AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. Model Organisms: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise. Model Internals and Interpretability: Advancing our understanding of the internal workings of large language models to enable more targeted interventions and safety measures. Safeguards Research: Developing robust defenses against adversarial attacks, comprehensive evaluation frameworks for model safety, and automated systems to detect and mitigate potential risks before deployment. AI Welfare: Improving our understanding of potential AI welfare and developing related evaluations and mitigations. AI security & frontier red-teaming Stress-testing frontier models to understand the full extent of their current capabilities in fields such as cybersecurity, robotics or cryptography. ML systems & reinforcement learning Improving how frontier models are trained and building the infrastructure behind that research, from model architecture, optimizers and training data to accelerator simulators, hardware backends and RL environment pipelines. For a fuller picture of the questions we care about, see our Recommendations for Technical AI Safety Research Directions and recent publications from our Alignment , Interpretability and Frontier Red teams. Logistics Duration: Placements are six weeks, three months or six months, depending on team fit and candidate preferences. Other lengths between three and six months are possible by exception. Location: This application is for a remote UK position, with the option to work from our London office. However, we prefer that Residents work from our San Francisco office, where most of our research staff is based, but remote participation is possible, especially for shorter placements. Most full-time research roles at Anthropic require relocation to San Francisco. Remote participants need to be based in a country where Anthropic can hire. Commitment: Full-time role for the duration of the residency. Compensation: £265,000 to £375,000/year pro-rated for the duration of the residency + benefits Visa sponsorship: We sponsor visas for placements of three months or longer. For six-week placements we encourage remote participation from a country where Anthropic can hire. Applicants may also be considered for the Anthropic Fellows Program . 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: £265,000 — £375,000 GBP Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Anthropic Residency is our paid, fixed-term research program, with placements lasting between six weeks and six months. We are looking for people who have led ambitious work in a variety of technical fields and want to transition to full-time work focused on making sure AI systems are safe and beneficial for all of humanity. If you are a professor in a quantitative discipline, a technical founder or a staff-level engineer and want to transition to work on transformative AI, we want to hear from you. Background in machine learning is not required. What to expect A concrete, scoped project matched to your background, with direct mentorship from Anthropic researchers Access to Claude models and GPU compute Connection to the broader AI safety and security research community Interview process The interview process will include an initial application, recruiter screen, technical assessment, research discussion and a reference check. Applications for this round close on November 22, 2026 (11:59 PM PT). We expect to make offers in January 2027. You may be a good fit if you Are motivated by making sure AI is safe and beneficial for society as a whole Are excited to transition into working on empirical AI research full-time Have led ambitious work in a variety of technical fields (professor in a quantitative discipline, a technical founder or a staff-level engineer) Thrive in fast-paced, collaborative environments Can implement ideas quickly and communicate clearly Strong candidates may also Have experience authoring research papers in machine learning, NLP, or AI safety Have experience with LLMs, reinforcement learning or Kubernetes clusters and complex shared codebases Mentors and research areas Potential Anthropic mentors include: Sara Price : leads the Alignment Training team; background in data science Ethan Perez : leads the Alignment Science team; background in machine learning Evan Hubinger : leads the Alignment Stress-Testing team; formerly at The Machine Intelligence Research Institute (MIRI) Samuel Marks : leads the Scalable Oversight team; background in mathematics Elana Simon : researches the interpretability of language models and biological models; background in biomedical informatics Belinda Li : researches how language models represent the world, users, and themselves; background in natural language processing (PhD, MIT) Jack Lindsey : leads the Model Psychology team; background in theoretical neuroscience Nicholas Carlini : researches adversarial machine learning and AI security; previously at DeepMind and Google Brain Jascha Sohl-Dickstein : works at the intersection of safety and pretraining; background in physics and neuroscience, formerly Principal Scientist at Google Brain Residents will work on empirical research questions in collaboration with Anthropic's research teams. Areas we are particularly interested in include: AI safety & alignment Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains. Adversarial Robustness and AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. Model Organisms: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise. Model Internals and Interpretability: Advancing our understanding of the internal workings of large language models to enable more targeted interventions and safety measures. Safeguards Research: Developing robust defenses against adversarial attacks, comprehensive evaluation frameworks for model safety, and automated systems to detect and mitigate potential risks before deployment. AI Welfare: Improving our understanding of potential AI welfare and developing related evaluations and mitigations. AI security & frontier red-teaming Stress-testing frontier models to understand the full extent of their current capabilities in fields such as cybersecurity, robotics or cryptography. ML systems & reinforcement learning Improving how frontier models are trained and building the infrastructure behind that research, from model architecture, optimizers and training data to accelerator simulators, hardware backends and RL environment pipelines. For a fuller picture of the questions we care about, see our Recommendations for Technical AI Safety Research Directions and recent publications from our Alignment , Interpretability and Frontier Red teams. Logistics Duration: Placements are six weeks, three months or six months, depending on team fit and candidate preferences. Other lengths between three and six months are possible by exception. Location: We prefer that Residents work from our San Francisco office, where most of our research staff is based, but remote participation is possible, especially for shorter placements. Most full-time research roles at Anthropic require relocation to San Francisco. Remote participants need to be based in a country where Anthropic can hire. Commitment: Full-time role for the duration of the residency. Compensation: $350,000 to $500,000/year pro-rated for the duration of the residency + benefits Visa sponsorship: We sponsor visas for placements of three months or longer. For six-week placements we encourage remote participation from a country where Anthropic can hire. Applicants may also be considered for the Anthropic Fellows Program . 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: $350,000 — $500,000 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: Remote (US) About the company Hi, we're Ondo Finance. Our mission is to provide institutional-grade, blockchain-enabled investment products and services. We have both a technology arm that develops decentralized finance technology, and an asset management arm that creates and manages tokenized funds. We are the global leader in tokenized treasuries, tokenized stocks and ETFs, and are building the future of institutional-grade financial services onchain. Founded by folks from Goldman Sachs Digital Assets Team, we’re backed by some of the best investors in the world including Founders Fund, Coinbase Ventures, Pantera Capital, Tiger Global, and more. We are currently the leaders in the space in terms of AUM and are well capitalized to continue growing the firm. We're fully remote, with team members across the U.S. About the role Ondo's user research team is small but mighty, and works horizontally across the whole product suite, not inside a single pod. We're hiring a senior quantitative user researcher to build and lead quantitative research across the portfolio. You'll set your own UXR strategy with minimal guidance, take on the hardest decision-shaping questions whichever team they come from, and answer them with evidence that holds up at scale. What You'll Do Own the research intake and quant roadmap. Field research questions from product, design, GTM and leadership. Turn vague asks into answerable questions, decide which need quantitative evidence (and which don't), and prioritize where evidence most reduces risk on our biggest bets. Answer the big questions before launch. Use MaxDiff and conjoint to show which features, benefits and messages actually drive decisions. Design pre-launch experiments (stimulus tests, matched cohorts, vignettes, threshold studies) with decision rules set before fielding, and pretest instruments with cognitive interviews. Build measurement and segments that last. Adapt or develop validated scales for trust, perceived security and comprehension, track them across products and markets, and turn our user profiles into statistically validated, sized segments. Get data you can trust, and connect it to behavior. Design sampling, translation and fraud controls for a global, crypto-native audience, and partner with data science to link survey data with product data. Evaluate AI-assisted experiences. Design human evaluation for AI-assisted finance features: rubrics, rater reliability, and whether user trust matches how reliable the system actually is. Be leadership's partner for evidence. Present findings as recommendations with effect sizes, confidence and what would change the call. Give quick, right-sized answers to ad-hoc leadership questions, whether that's existing data, a fast pulse survey or a full study. Set the standards that let PMs and designers run sound lightweight surveys or data-driven validation themselves. Requirements 7+ years of UX or applied research experience, including at least 5 years leading quantitative studies end to end, from study design through recommendation. Experience leading quantitative research studies for financial products (e.g., brokerage, trading, banking, payments, wealth or lending). A self-starter who operates with minimal guidance: you scope ambiguous problems, set your own priorities, and drive studies to a decision. Deep survey science expertise: sampling and weighting, instrument design, bias control, data-quality screening, and programming in Qualtrics or similar. Hands-on experience designing and analyzing MaxDiff and/or conjoint studies. Strong applied statistics: regression, power analysis, and experimental and quasi-experimental design. Fluency in R or Python for analysis and visualization. You have an existing AI-assisted research setup, from drafting survey instruments to writing and reviewing analysis code, and you proofread/validate every output with rigor. A track record of quantitative work that changed a product or business decision, and the ability to explain uncertainty clearly to executives and non-researchers. Nice to Have Experience with crypto, onchain or tokenized-asset products. A master’s or PhD in a quantitative field such as statistics, survey methodology, behavioral economics, or marketing science. Depth in advanced methods, such as hierarchical Bayes and simulators, psychometric scale development, segmentation, pricing research, or SQL and multilevel modeling. Experience evaluating AI or LLM-powered products, such as human evaluation design, rubrics or rater reliability. Research across markets in LATAM, APAC or EMEA, including translating survey instruments. Responsible AI-native research workflows, such as using LLM tools to speed up instrument design, coding of open-ended responses or analysis. What we offer Competitive compensation including but not limited to salary, future token rights, and/or equity (according to your preferences) — We are well-funded and believe that great talent deserves great compensation. Full benefits (medical, vision, and dental) and flexible vacation policy (PTO). Remote-first team across many countries — You will be an early team member helping shape our vision, culture, and design practices. A+ colleagues — Our team includes alumni from: Goldman Sachs, Blackrock, Two Sigma, Bridgewater, SpaceX, AWS, Meta, Google, McKinsey, Circle, Uniswap. Best-in-class investors — We are proud to be backed by leading crypto experts and VCs, including Pantera Capital, Founders Fund and Coinbase Ventures.

SpAItial is looking for PhD Research Interns to explore 3D generation and reconstruction, develop and evaluate novel methods, and publish research findings.

Isomorphic Labs is looking for a Research Leader in Toxicology to lead safety assessment strategies, regulatory toxicology work, CRO partnerships, and AI-driven toxicology platform development.

— Обладатели исследовательской докторской степени в профильной области не допускаются. — Как правило, нужна магистратура или эквивалентная квалификация в естественных науках или науках о жизни и исследовательский опыт.

Location: San Francisco, CA 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 Anthropic's Life Sciences team is building a research group focused on biological discoveries by combining AI with hands-on biological research. We're seeking a research scientist who combines deep chemistry knowledge with machine learning expertise to join the team. Our goal is to speed up progress in the life sciences by an order of magnitude, and this role puts that mission into practice. You'll be a computational chemist who knows reactions, synthesis, and medicinal chemistry in depth and has hands-on experience training and evaluating machine learning models. Above all, you'll build the reinforcement learning environments, datasets, and evaluations that teach Claude chemistry. Working alongside our bench chemists and AI researchers, you'll turn real chemistry problems and experimental data into training tasks and measure whether the models get better at them. This role is fully on-site in the San Francisco Bay Area. Key responsibilities Design and build reinforcement learning environments for chemistry end to end, including task design, data curation, automated grading, and checks against shortcuts and data leakage Design and source new experimental datasets, environments, and evaluations with our bench chemists, and external research and academic partners Develop evaluations that measure model performance on real chemistry tasks, such as reaction outcome prediction, synthesis planning, structure elucidation, and compound design, and feed results back to research teams Run and analyze training experiments with AI research teams, diagnose where models fail at chemistry, and prioritize what to build next Ensure datasets and environments are high quality and well documented, including sources, train and test splits, and failure modes Communicate findings clearly to chemistry, AI research, and life sciences audiences Minimum qualifications PhD in chemistry, computational chemistry, or a related field Deep knowledge of organic and medicinal chemistry, including reactions, synthesis, and SAR, with experimental data as your ground truth Strong Python skills and solid machine learning fundamentals, with hands-on experience training and evaluating models Comfort navigating ambiguity and defining problems in a rapidly evolving research environment Ability to work independently while collaborating effectively across cross-functional teams, with strong written and verbal communication skills Preferred qualifications Experience with reinforcement learning, large language models, or building evaluations and benchmarks Track record of supporting drug discovery programs alongside medicinal and synthetic chemists Experience curating chemistry datasets from the literature, patents, or lab notebooks, including reaction, ADMET, and spectroscopic data Cheminformatics and molecular modeling skills, for example RDKit, docking, free energy calculations, or quantum chemistry Hands-on synthetic or medicinal chemistry experience at the bench Publications, patents, or open-source software demonstrating scientific impact 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: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Singapore Workplace: Hybrid About Cantina: Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning. About the Role: Cantina is expanding, and we're looking for a Research Scientist to join our growing Singapore team! In this role, you will drive foundational research on video generation models, taking ownership across the full research cycle and driving post-training research. Furthermore, you'll collaborate closely with data, infrastructure, and adjacent modeling teams to translate research findings into durable model improvements. What You’ll Do: - Build and maintain scalable systems for ingesting, preprocessing, and delivering large-scale video data for model training - Design and scale distributed data pipelines for preprocessing, dataset generation, and repeated dataset refreshes - Own workflow orchestration, job scheduling, monitoring, and failure recovery for large-scale data processing jobs - Implement and maintain containerized pipeline infrastructure using Kubernetes or equivalent orchestration systems - Optimize cloud-based data storage and movement across providers (AWS, GCS, or Azure) for cost, throughput, and operational efficiency - Define and implement best practices for dataset storage layout, versioning, caching, retention, and access patterns - Build tooling to support deduplication workflows at scale, including near-dedup pipelines over large video corpora - Research and develop distillation methods for large-scale diffusion and flow-based video generation models, including guidance distillation and adversarial distillation, with a focus on preserving or improving generation quality while reducing inference cost - Develop reward models and preference-based fine-tuning pipelines that align video generation quality with human judgments across dimensions such as aesthetics, motion quality, and prompt adherence - Analyze the relationship between base model behavior and post-training outcomes, and work with the foundation model team to inform pretraining decisions accordingly What You’ll Bring: - Strong hands-on experience building or scaling large-scale data systems or pipelines for machine learning workflows - Experience with distributed data processing frameworks such as PySpark or Ray, and orchestration tools such as Airflow or equivalent - Familiarity with containerization and container orchestration, including Docker and Kubernetes - Experience working with cloud-based data storage and compute (AWS, GCS, and/or Azure), including tradeoffs around cost, throughput, storage layout, and access patterns - Familiarity with video and media processing tools such as FFmpeg, PyAV, DALI, or OpenCV - Familiarity with multimodal or media data, including video, image, text, and audio - Strong research background in post-training methods for large-scale diffusion or flow-based generative models, with deep hands-on experience in distillation across both inference efficiency and quality preservation - Experience with reward modeling or preference-based fine-tuning for generative models, including RLHF, DPO or equivalent alignment approaches - Solid understanding of the interplay between pretraining and post-training, and how base model properties affect distillation and fine-tuning outcomes - Proficiency in Python and modern machine learning frameworks, with a strong preference for PyTorch or JAX - Track record of independent research, with the ability to drive projects from initial idea through experimental validation - Publications at top-tier venues (NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV) preferred - Good understanding of the practical challenges involved in building reliable, scalable, and reproducible data workflows for machine learning systems Benefits We Offer: - Competitive salary and generous company equity - Personal time off and paid holidays - Health insurance - Global travel insurance: Covers you when traveling internationally - Monthly spending stipend: $500 (~S$635) - Equipment: All equipment needed for your home office