Вакансии

Location: Seoul, South Korea 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 As a Regional Research Economist at Anthropic, you will collaborate with governments, academia, industry, and civil society in your region to measure and understand AI’s effects on the economy and explore research-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigor will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions. Our team combines rigorous empirical methods with novel measurement approaches. We’re building first-of-its-kind datasets tracking AI’s impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system ( Clio ), we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks. For this role, we’re looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI’s transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact. Key responsibilities Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region Advance research collaborations that answer country- or regional-specific economic impact questions Translate research insights into actionable recommendations for policy discussions Make fundamental contributions to the development and expansion of the Anthropic Economic Index , including country- and regional-specific analysis Design and collaborate on empirical research on AI’s economic effects with governments, academia, industry, and civil society in your region Develop new methodological approaches, in collaboration with partners in your region, for studying AI’s impact on labor markets and the future of work; productivity and task transformation; economic inequality and displacement; industry-specific disruption and adaptation; and aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders Minimum qualifications PhD in Economics Strong track record of empirical research, particularly studies combining novel data sources and economic theory or implementing frontier methods in causal inference and machine learning Demonstrated experience working in, and relevant relationships across, the region Proficiency in Python, R, SQL, or similar tools for large-scale data analysis Demonstrated ability to lead complex research projects from conception to publication Demonstrated ability to communicate technical findings to diverse audiences Demonstrated ability to build relationships across academic, policy, and industry communities Preferred qualifications Experience relevant to the study of AI’s impact on the economy, such as labor market analysis and occupational change; task-based approaches to technological transformation; large-scale data analysis and econometric methods; large language models for social science research; policy-relevant economic research; experimental and quasi-experimental methods for causal inference; macroeconomic modeling and time series forecasting; or agent-based modeling and large-scale simulation Experience working with novel datasets and measurement systems Comfort learning new technical tools and frameworks Strong interest in ensuring AI development benefits humanity Comfort working with AI systems and ability to think critically about their capabilities and limitations Representative projects How Australia Uses Claude: Findings from the Anthropic Economic Index Anthropic Economic Index Report: Economic Primitives Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption Estimating AI productivity gains from Claude conversations The Anthropic Economic Index 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: Sydney, Australia 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 As a Regional Research Economist at Anthropic, you will collaborate with governments, academia, industry, and civil society in your region to measure and understand AI’s effects on the economy and explore research-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigor will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions. Our team combines rigorous empirical methods with novel measurement approaches. We’re building first-of-its-kind datasets tracking AI’s impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system ( Clio ), we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks. For this role, we’re looking for candidates who can combine rigorous economic analysis with novel measurement approaches to understand AI’s transformative effects on the economy. The ideal candidate will be comfortable working at the intersection of empirical economics, technological change, and policy impact. Key responsibilities Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region Advance research collaborations that answer country- or regional-specific economic impact questions Translate research insights into actionable recommendations for policy discussions Make fundamental contributions to the development and expansion of the Anthropic Economic Index , including country- and regional-specific analysis Design and collaborate on empirical research on AI’s economic effects with governments, academia, industry, and civil society in your region Develop new methodological approaches, in collaboration with partners in your region, for studying AI’s impact on labor markets and the future of work; productivity and task transformation; economic inequality and displacement; industry-specific disruption and adaptation; and aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders Minimum qualifications PhD in Economics Strong track record of empirical research, particularly studies combining novel data sources and economic theory or implementing frontier methods in causal inference and machine learning Demonstrated experience working in, and relevant relationships across, the region Proficiency in Python, R, SQL, or similar tools for large-scale data analysis Demonstrated ability to lead complex research projects from conception to publication Demonstrated ability to communicate technical findings to diverse audiences Demonstrated ability to build relationships across academic, policy, and industry communities Preferred qualifications Experience relevant to the study of AI’s impact on the economy, such as labor market analysis and occupational change; task-based approaches to technological transformation; large-scale data analysis and econometric methods; large language models for social science research; policy-relevant economic research; experimental and quasi-experimental methods for causal inference; macroeconomic modeling and time series forecasting; or agent-based modeling and large-scale simulation Experience working with novel datasets and measurement systems Comfort learning new technical tools and frameworks Strong interest in ensuring AI development benefits humanity Comfort working with AI systems and ability to think critically about their capabilities and limitations Representative projects How Australia Uses Claude: Findings from the Anthropic Economic Index Anthropic Economic Index Report: Economic Primitives Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption Estimating AI productivity gains from Claude conversations The Anthropic Economic Index 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.

Чем предстоит заниматься: Активный поиск ( сорсинг ) IT -кандидатов по сложным запросам разработчиков, DevOps , Data Scientists , QA и других специалистов. Работа с международными площадками: LinkedIn (включая X-Ray search), GitHub, Stack Overflow, Telegram-чаты, специализированные англоязычные форумы.

Bitdeer is looking for a research scientist or research engineer to research, implement, measure, and ship inference-serving system improvements.

Location: Москва Приглашаем исследователей в области машинного обучения в команду Рекомендательных систем и персонализации Центра практического ИИ. Центр практического искусственного интеллекта - стратегическое подразделение Сбера, создающее наукоемкие технологии. Мы создаем новые алгоритмы рекомендательных систем и адаптируем SOTA-подходы для задач банка и компаний-партнеров, помогаем бизнесу внедрять новые технологии. Также мы разрабатываем собственные open-source фреймворки и публикуем результаты наших исследований на международных конференциях уровня A/A\*. Приглашаем присоединиться к исследованиям и прикладным проектам в области рекомендательных технологий, DL-моделей для последовательных данных и подходов на стыке LLM и RecSys. Первый этап отбора на эту вакансию – общение с AI-рекрутером. После отклика ждите сообщение от него в сберчате, диалог займёт примерно 10 минут. Задача AI-рекрутера — уточнить недостающие детали и ускорить рассмотрение вашей кандидатуры. AI-рекрутер только начинает свой путь, поэтому просим относиться с пониманием. Ваш опыт и участие помогут сделать его удобным и полезным для всех! Обязанности ### Наши задачи: * развиваем библиотеку для рекомендательных систем RePlay [https://github.com/sb-ai-lab/RePlay](https://github.com/sb-ai-lab/RePlay) * разрабатываем и улучшаем алгоритмы рекомендательных систем * разрабатываем и обучаем трансформерные модели на последовательностях событий на последовательностях событий на банковских данных * проводим исследования в области sequential recommendations, LLM для рекомендаций, foundation models для событийных данных sequential recommendations и генеративных рекомендаций * разрабатываем и внедряем AI агенты для банка * пишем статьи и выступаем на ведущих мировых и российских конференциях. Требования ### Мы ожидаем: * опыт работы от 2 лет в области, связанной с RecSys / DL / NLP * умение писать читаемый и хорошо структурированный код на python * знание стандартных библиотек и фреймворков (numpy, pandas, polars, scikit-learn, pytorch, pytorch-lightning, transformers) * навыки организации и воспроизводимого проведения ML-экспериментов (Hydra, Сlearml, Mlflow, W&B, Neptune) * опыт разработки и обучения моделей с помощью pytorch * знание математики, глубокое понимание классического ML и современных методов DL, широкий кругозор в ML в целом * понимание современных Transformer-based архитектур для работы с последовательностями * знание ключевых рекомендательных подходов и методов их оценки * умение читать, анализировать и воспроизводить научные статьи. Будет плюсом: * опыт успешного участия в ML соревнованиях и хакатонах * опыт написания научных статей, наличие публикаций * понимание принципов работы современных LLM и LLM-агентов. Условия ### Мы предлагаем: * комфортный современный офис г. Москва, рядом с метро Кутузовская * гибридный формат работы * ежегодный пересмотр зарплаты и годовая премия * корпоративный спортзал и зоны отдыха * 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.

Location: Serbia; Cyprus; London, United Kingdom; Amsterdam, Netherlands; Singapore; Georgia We are looking for a Head of ML / Head of Quant Research to take full ownership of developing and scaling machine learning trading strategies in crypto markets (Spot / Perpetuals). You will take over a live, operating production ML trading system with existing Capital Under Management and lead a dedicated research team. Key Responsibilities Full Ownership: Take complete control of the research pipeline, model architecture, signal generation, and risk limits. Alpha Generation: Design, backtest, and deploy new profitable ML models and quantitative trading strategies. Execution & Scaling: Optimize execution algorithms, refine live strategy performance, and scale capital under management. Leadership: Lead, mentor, and grow a team of quant researchers and developers. Requirements Education & Mathematical Background: Degree in CS / Math / Data Science from a top-tier university (MIPT, HSE, MSU, SPbSU, ITMO, YSDA, or international equivalents). Strong foundation in probability, statistics, linear algebra, and algorithms. Tech Stack & Hard Skills: Python (NumPy, Numba). PyTorch or JAX (for the ML track) OR advanced backtesting/quantitative modeling frameworks (for the Quant track). Proven track record of developing profitable ML models or quantitative trading strategies in production. Nice to Have: Experience in crypto/HFT/algorithmic trading (Order Book dynamics, L2/L3 data, funding rate arbitrage, liquidations). Proficiency in C++ (reading, profiling, and optimizing performance). Competitive programming / Kaggle achievements (IMO, IOI, ICPC, Codeforces, Kaggle Master/GM) or top-tier publications (NeurIPS, ICML, ICLR). English: A2+ (Internal team communication is in Russian; fluent spoken English is not required). Benefits Competitive fixed salary. PnL share (individual agreement). Direct influence on risk limits, capital allocation, and research roadmap. Remote work or office in Serbia, official contracting via Dubai / Serbia.

-Проводить глубокий research в рамках поставленных задач. -Изучение и анализ JS скриптов на сайтах.

Location: Global, EU We are the creators of a new fintech era! Our mission is to change this world by making blockchain accessible to everyone in everyday life. WhiteBIT is a global team of over 1,200 professionals united by one mission — to shape the new world order in the Web3 era. Each of our employees is fully engaged in this transformative journey. We work on our blockchain platform, providing maximum transparency and security for more than 8 million users worldwide. Our breakthrough solutions, incredible speed of adaptation to market challenges, and technological superiority are the strengths that take us beyond ordinary companies. Our official partners include the National Football Team of Ukraine, FC Barcelona, Lifecell, FACEIT and VISA. Requirements Minimum 10 years of relevant experience in corporate strategy, strategic finance, investment, corporate development, management consulting, private equity / venture capital, investment banking or a comparable analytical leadership role. Demonstrated experience developing or maintaining enterprise or group-level strategy and translating complex analysis into clear choices for senior decision-makers. Strong portfolio mindset, with the ability to assess strategic fit, concentration, adjacency, risk, expected value and trade-offs across multiple businesses, products, markets and initiatives. Strong financial and investment analysis skills, including business-case review, valuation logic, unit economics, scenario analysis and sensitivity testing. Proven ability to evaluate new projects, market-entry plans, strategic initiatives and investment theses independently and to challenge assumptions constructively. Excellent research and intelligence capabilities, including the ability to synthesize market, competitor, regulatory, technology and customer signals into decision-relevant implications. Experience preparing executive and Investment Committee / Board-level materials, recommendations and concise decision memos. Prior experience leading and developing a high-performing strategy, research or analytical team, with strong quality-control standards. Experience in financial services, FinTech, digital assets, payments, banking, brokerage, investment or financial infrastructure is strongly preferred. Excellent written and verbal communication, stakeholder management and presentation skills; able to build trust while maintaining independent judgment. High professional integrity, intellectual curiosity, discretion and the confidence to provide an evidence-based challenge to senior stakeholders. Advanced degree or relevant professional qualification is a plus. Responsibilities Group Strategy & Portfolio Stewardship Own and maintain the group strategy process, including the strategic narrative, priorities, key choices, assumptions and periodic refreshes. Maintain a portfolio-wide view of businesses, products, markets, capabilities and strategic initiatives, and identify imbalances, gaps, duplication, concentration risk and adjacency opportunities. Develop evidence-based recommendations on where the group should focus management attention, strategic resources and future investment, while preserving the Investment Committee's decision authority. Ensure that major roadmaps and programs remain coherent with the approved group strategy and portfolio logic. Research, Intelligence & Strategic Insight Set the strategic research agenda based on the group's highest-priority decisions and uncertainties. Build and maintain structured intelligence on markets, competitors, regulation, technology, customer behavior, business models and relevant macro trends. Convert research findings into implications, scenarios, strategic options and concise recommendations rather than stand-alone information reporting. Establish strong standards for source quality, analytical rigor, assumptions, fact checking and institutional knowledge retention. Value Creation Opportunities Continuously identify and prioritize value creation opportunities across the existing portfolio, including growth, cross-business synergies, product / market adjacencies, partnerships, operating-model improvements and other strategic moves. Structure each opportunity into a clear thesis covering expected value, strategic rationale, risks, dependencies, required capabilities, sequencing and success measures. Work with the Portfolio Management Team and Business Owners to convert approved opportunities into roadmaps and executable initiatives without taking over day-to-day execution ownership. Evaluation of New Projects, Markets & Strategic Moves Lead independent strategic review of new project proposals and market plans before they are submitted for approval. Assess strategic fit, market attractiveness, competitive position, economics, risk, execution readiness, alternatives and portfolio implications; test critical assumptions through scenarios and sensitivity analysis. Formulate a clear recommendation - proceed, revise, stage, defer or stop - and define the key conditions or milestones required for success. Partner with the M&A and Deal Team on strategic fit, investment thesis and portfolio impact of potential acquisitions, divestments and other transactions, while the Deal Team retains transaction execution ownership. After-Action Review & Portfolio Learning Establish a systematic after-action review approach for major strategic actions, initiatives and completed deals. Compare actual outcomes with the original strategic thesis, expected economics, risk assumptions, milestones and value-creation plan, and assess the resulting effect on the group portfolio. Capture lessons learned, identify repeatable patterns and feed findings back into strategy, evaluation frameworks and future recommendations. Investment Committee & Executive Decision Support Prepare clear, concise and decision-grade strategic recommendations for Investment Committee and senior leadership consideration. Work with the Board / IC Secretary to ensure strategic materials are complete, internally consistent and framed around the decision required, alternatives, trade-offs and implications. Support interpretation of execution feedback and result reporting from the Portfolio Management Team and Business Owners, focusing on strategic implications and any need to revisit prior assumptions or decisions. Maintain a disciplined distinction between analysis / recommendation, governance decision-making and execution ownership. Team Leadership & Functional Excellence Lead, coach and develop the Strategy and Research Team; allocate work against the highest-value strategic questions and maintain clear accountability for output quality and deadlines. Build repeatable methods, templates and analytical standards for strategy development, market / project evaluation, portfolio review, research and after-action analysis. Create a high-trust culture that values intellectual honesty, constructive challenge, clear writing, collaboration and decision usefulness. Working terms Immerse yourself in Crypto & Web3: Master cutting-edge technologies and become an expert in the most innovative industry. Work with the Fintech of the Future: Develop your skills in digital finance and shape the global market. Take Your Professionalism to the Next Level: Gain unique experience and be part of global transformations. Drive Innovations: Influence the industry and contribute to groundbreaking solutions. Join a Strong Team: Collaborate with top experts worldwide and grow alongside the best. Work-Life Balance & Well-being: Modern equipment. Comfortable working conditions, and an inspiring environment to help you thrive. 24 calendar days of paid leave. Additional days off for national holidays. With us, you’ll dive into the world of unique blockchain technologies, reshape the crypto landscape, and become an innovator in your field. If you’re ready to take on challenges and join our dynamic team, apply now and start a new chapter in your career! Let’s Build the Future Together! WhiteBIT offers all candidates an equal opportunity to join the team. All hiring decisions are made without regard to race, national origin, gender identity or sexual orientation, age, religion, disability, medical condition, marital status, familial status, veteran status, or any other legally protected characteristic of an individual. Your privacy matters to us. You can learn more about how we handle your personal data with regard to your application in our Candidate Privacy Notice .

Mistral is looking for a Research Engineer GPU Performance to optimize generative AI model training and inference on GPUs.

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 Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is a large distributed system: training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts. As an engineer in RL Engineering, you'll work on keeping that system secure as it scales. This is a hands-on engineering role. You'll work in the RL codebase and the infrastructure underneath it, alongside the engineers and researchers who build and use it. The system is large and changes as fast as the research does, so security work here has to keep up with that pace without costing performance or velocity. We're hiring from two backgrounds: security engineers who want to work on large-scale ML systems, and ML systems or research engineers who want to work on security. Strong candidates have depth in one and real interest in the other. Key responsibilities Design, build, and operate security controls for RL training systems and the infrastructure they run on Work across the stack (orchestration, environments, training, inference) wherever the work is needed Review designs and code across the RL stack, find security problems, and fix them Build shared libraries and tooling that other RL engineers and researchers build on Build the observability needed to understand what these systems are doing Work with researchers and performance engineers to make sure security changes preserve training correctness and performance Write clear design documents for what you build Minimum qualifications Strong software engineering skills in Python and at least one systems language such as Rust, C++, or Go Experience designing, building, and operating large-scale distributed systems or security systems in production Strong understanding of security fundamentals Working knowledge of Linux, containers, and cloud infrastructure Experience debugging complex problems across many hosts and services Ability to reason about tradeoffs between security, performance, and reliability Strong written communication, including design documents Preferred qualifications Experience running ML training or inference infrastructure at scale Experience with infrastructure security, such as isolation, access control, networking, or identity Experience with container orchestration such as Kubernetes, and with sandboxed or virtualized code execution at scale Experience building observability for large fleets Experience supporting research teams or other fast-moving internal users Familiarity with reinforcement learning or large language model training workloads 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: $320,000 — $405,000 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: Paris; London ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE As a Research Engineer on the Latency & Throughput team, you will push the frontier of LLM inference by researching and prototyping techniques that reduce latency and increase throughput — from speculative decoding and quantization to KV compression and new attention variants. The team sits at the intersection of research and production: you will take ideas from recent literature, form hypotheses, run experiments, and ship the techniques that prove out into our serving stack. This role sits between our inference engineers, who own the production serving stack, and our research scientists, who focus on paper-level contributions. You will be more science-focused than a pure engineer: you are expected to generate new ideas, keep up with the state of the art, and implement proof-of-concepts that bridge the gap between academic results and production impact. Some techniques you explore will be lossy or require integration into training — retraining models, tuning architectures, or training auxiliary models to improve inference. You will work closely with the Inference Foundation and Kernels teams, who turn your validated techniques into production recipes, and with pretraining and RL teams when your work touches model training. Success is measured by demonstrated latency or throughput gains, first at small scale, then adopted in production. What You Will Do - Research and prototype inference techniques — speculative decoding, quantization, KV compression, watermarking, and new model architectures — by reading recent literature and forming testable hypotheses. - Design and run experiments to validate or refute ideas, iterating quickly on small-scale setups before proposing production integration. Demonstrate clear latency or throughput gains without unacceptable quality loss. - Collaborate with the Inference Foundation team to integrate validated techniques into the vLLM-based serving stack. - Partner with pretraining and RL teams when techniques require co-training, retraining, or training auxiliary models to improve inference. Build the right tooling and validation platforms to facilitate AI-driven inference research. What We're Looking For - A strong ML background with solid knowledge of LLM training techniques — architecture, tokenization, fine-tuning, and evaluation. - Hands-on experience with Python and PyTorch; you write clean, experimental code and iterate fast. JAX is acceptable with strong Python proficiency. C++ and Rust are not required, CUDA and GPU knowledge is expected but hands-on experience is not required. - Research experience of some form: a thesis, publications, a dedicated research project, or efficiency-oriented work in a lab or industry research setting. A PhD is not required, but we are looking for genuine research depth. - A track record of conducting experiments: forming hypotheses, designing controlled comparisons, and drawing clear conclusions from results. - Familiarity with the state of the art in LLM inference — you know what has been tried, what works, and where the open problems are. - Self-starter, low-ego, and collaborative. You are comfortable with ambiguity, negative results, and are eager to take matters into your own hands. - Inference or serving experience is a plus, not a requirement. Prior work with vLLM, production LLM deployments, or serving systems will help you ramp up faster. Location and Remote This role is based in our Paris or London offices (hybrid). We will prioritize candidates who reside in the Paris area or are open to relocating. We strongly believe in the value of in-person collaboration to foster strong relationships and seamless communication within our team. For senior profiles, we will also consider remote candidates based in France. In that case, we ask all new hires to visit our Paris office: - For the first week of their onboarding (accommodation and travel covered) - Then at least 3 days per month WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Paris, France About Allucent™ At Allucent™, our mission is to shine a light on new therapies that improve lives. When you join our team, you’ll use your unique skills, expertise, and knowledge to forge meaningful partnerships with clients while helping them turn groundbreaking ideas into life-changing treatments. If you’re passionate about advancing pharmaceuticals and biologics, fueled by an entrepreneurial spirit, and eager to collaborate with top minds across science, business, and operations, we’d love to connect. Together we can accelerate innovation and grow side by side, making a last impact on patients worldwide. Together we SHINE . Find more information about our values. The role Bring your monitoring expertise to the forefront of innovation. We are looking for a Clinical Research Associate (CRA) to join our A-team. As a CRA at Allucent™, you will independently control and monitor investigational sites, pro-actively detect issues, provide solutions to ensure clinical studies are performed according to the trial protocol and in compliance with SOPs, applicable regulations, and the principles of Good Clinical Practice. As a CRA , you will take the lead on monitoring activities, owning your sites and relationships with investigators. You’ll be the bridge between sponsor and site, ensuring trial integrity while being supported by a collaborative, experienced team. This includes work related to regulatory affairs, site activation processes—including contracting and start-up activities—to ensure smooth and compliant study execution. You will travel throughout France. Main responsibilities: Independently manage all aspects of monitoring for assigned clinical trials across study phases, including site initiation, routine monitoring, and close-out visits. Ensure compliance with protocols, GCP, ICH, SOPs, and applicable regulatory requirements. Build strong site relationships , acting as a primary point of contact and ensuring high-quality data collection. Identify and resolve site issues , escalating as needed to maintain trial integrity and patient safety. Activities around regulatory affairs, site activation and study-startup. Requirements To be successful you will possess: You’re an experienced CRA ready to take the next step with a company that truly values your expertise and independence. You thrive in an agile, collaborative environment and want to be part of a team making a real impact. Experience in leading monitoring activities in complex trials with a minimum of 2 years’ experience. Strong understanding of ICH-GCP and regulatory guidelines . Clear and confident communicator in English and French. Comfortable working independently and managing priorities. Willingness to travel, as required (8 DOS per month). Benefits Benefits of working at Allucent include: Comprehensive benefits package per location Competitive salaries per location Departmental Study/Training Budget for furthering professional development Flexible Working hours (within reason) Participation in our enriching Buddy Program as a new or existing employee Internal growth opportunities and career progression Financially rewarding internal employee referral program Eligibility for our Spot Bonus Award Program in recognition of going above and beyond on projects Eligibility for our Loyalty Award Program in recognition of loyalty and commitment of longstanding employees Disclaimers: *Our in-office work policy encourages a dynamic work environment, prescribing 2 days in office per week for employees within reasonable distance from one of our global offices . “The Allucent Talent Acquisition team manages the recruitment and employment process for Allucent (US) LLC and its affiliates (collectively “Allucent”). Allucent does not accept unsolicited resumes from third-party recruiters or uninvited requests for collaboration on any of our open roles. Unsolicited resumes sent to Allucent employees will not obligate Allucent to the future employment of those individuals or potential remuneration to any third-party recruitment agency. Candidates should never be submitted directly to our hiring managers, employees, or human resources.” #LI-BL1

Размечать карточки компаний по заданным признакам (например, pricing power по шкале 0/1/2, уровень долговой нагрузки, зависимость от одного клиента) с обязательной ссылкой на источник. Проверять выводы AI-агента по первичке: читать отчёт или транскрипт, сравнивать с оценкой модели, фиксировать расхождения и их причину.

Location: United Kingdom; United States; Poland; Bulgaria Workplace: Remote ABOUT ELEVENLABS ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $22B - multiples of 11, always. We have expanded from voice into three main platforms: - ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. - ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. - ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. HOW WE WORK - High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. - Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. - AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. - Excellence everywhere: Everything we do should match the quality of our AI models. - Global team: We prioritize your talent, not your location. WHAT WE OFFER - Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. - Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities. - Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend. - Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose. - Annual team offsite: Each year, we bring your entire team together in a new location - past offsites have included Croatia, Italy and Cancún - Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend. ABOUT THE ROLE We are looking for a Research Engineer to join the research team at ElevenLabs, focused on the data infrastructure that powers our frontier AI models. The quality of our models is bounded by the quality and scale of the data behind them, and you will own the systems that make world-class data possible. You will thrive in this role if you enjoy:   - Building large-scale data pipelines for collecting, processing, filtering, and transforming datasets used to train state-of-the-art models. - Training models used in our data processing pipelines, such as classifiers, quality filters, and labeling models. - Designing data curation strategies such as deduplication, quality scoring, labeling, and augmentation that measurably improve model performance. - Creating tooling and infrastructure that lets researchers explore and train on massive datasets quickly and reliably.   REQUIREMENTS We do not require any formal certifications or degrees. Instead, we are seeking enthusiastic engineers who can showcase solving impressively hard problems with artifacts such as past projects, designs, or GitHub contributions. Ideally, you bring:   - Experience building data-intensive systems, ideally in support of machine learning training pipelines. - Strong engineering skills in distributed data processing at scale (e.g., Kubernetes, or custom pipelines over large datasets). - The capacity to autonomously evaluate how data quality, composition, and curation affect model outcomes, and to build the tooling to measure it.   Bonus: Experience building or operating web crawlers.   LOCATION This role is remote and can be executed globally. If you prefer, you can work from our offices in London, New York, San Francisco, and Warsaw.   #LI-Remote We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

Aleph Alpha is looking for Senior AI Researchers to develop and evaluate post-training methods that reduce LLM hallucinations and improve reliability.

Location: London Workplace: Hybrid ABOUT NIANTIC SPATIAL We are building for the >80% of economic activity that happens beyond the reach of screens. AI has learned from the text, images and video online, but it still lacks an accurate understanding of physical space. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. ABOUT THE ROLE You'll help build the geometric foundation of the next-generation world map — joining our World Map Research Engineering team (Geospatial Alignment) as a Research Engineer or Senior Research Engineer. This is an end-to-end applied research role that spans from strong engineering and data-systems work to R&D in 3D deep learning, transformers, and foundation models. You'll develop new algorithms, produce the research data and evaluation assets needed to advance them, and engineer the resulting capabilities into dependable production systems. The World Map team works with heterogeneous captures from phones and handheld devices, aerial imagery, LiDAR, and 360 cameras, as well as external geographic and elevation data. The central challenge is to harmonize these data sources, quantify uncertainty, and maintain consistency as the map evolves. You'll work at the intersection of cutting-edge research and scalable engineering — developing new approaches to geospatial registration, correspondence, and geometric optimization, then productionizing these technologies to directly improve Niantic Spatial's world model. What You'll Do - Geospatial Registration — Develop and advance algorithms for world-scale georeferencing and registration across imagery, 3D reconstructions, point clouds, and geographic reference data. - 3D Geometry & Correspondence — Build and improve methods spanning multi-view geometry, SfM, SLAM, feature matching, learned correspondence, bundle adjustment, point-cloud registration, and ICP. - Data & Evaluation — Create the data and evaluation flywheel for world-scale mapping — design and maintain large-scale datasets, pipelines, benchmarks, and evaluation methodologies that expose hard failure modes, accelerate research iteration, and support production. - Learning-Based 3D Reasoning — Explore and develop learning-based approaches for geospatial understanding, combining transformers and 3D foundation models with geometric priors and uncertainty modeling. - Production Robustness — Design robust solutions for challenging real-world conditions: sparse or noisy GPS, changing appearance, inconsistent reconstruction quality, large geographic extents, and imperfect reference maps. - Cross-Functional Collaboration — Partner with leading researchers in visual localization, 3D computer vision, and mapping — as well as engineering and product teams — to identify high-impact problems and turn research breakthroughs into end-to-end production systems. - Research Communication — Share results clearly through technical writing, design reviews, and internal presentations; contribute to publications and open research where appropriate. WHAT YOU'LL BRING - Bachelor's or Master's degree in Computer Science, Robotics, Machine Learning, Photogrammetry, or a closely related field — or equivalent research or industry experience. - Strong grounding in 3D computer vision, machine learning, robotics, photogrammetry, or a closely related area. - Demonstrated experience with 3D geometry and several relevant areas — multi-view reconstruction, SfM, SLAM, camera pose estimation, point-cloud registration, image-based localization, georeferencing, or sensor fusion. - The ability to formulate ambiguous real-world problems, choose the right mathematical or learning-based tools, and evaluate solutions rigorously. - Strong Python skills and experience with modern ML and scientific-computing libraries (PyTorch, NumPy, SciPy). - Strong software engineering skills — you can turn research prototypes into reliable, scalable, and maintainable systems. - A track record of taking an algorithm from research idea and experimental prototype through evaluation, benchmarking, and deployment on real-world data. - Clear written and verbal communication; able to collaborate effectively across research and engineering disciplines. NICE TO HAVE - PhD in computer vision, robotics, machine learning, photogrammetry, geodesy, remote sensing, or a related field — not required, but valued. - A strong publication record or active involvement in the research community at venues such as CVPR, ICCV, ECCV, NeurIPS, ICLR, SIGGRAPH, 3DV, ICRA, or RSS. - Experience with learning-based approaches for visual or 3D understanding — transformers, point transformers, foundation models, or methods combining learned representations with explicit geometric priors. - Experience with aerial or satellite imagery, GNSS/GPS, geodesy, mapping systems, or large-scale spatial data. - Evidence of technical leadership, mentorship, or successful cross-functional delivery. COMPENSATION & BENEFITS Base salary: Competitive market rate. Compensation also includes an annual bonus, equity, and a comprehensive benefits package. LOCATION & WORK MODEL This role is based in our London office, with three days per week in office. We welcome applications from candidates who require visa sponsorship. INCLUSIVE APPLICATION We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed — you may be exactly who we're looking for. EQUAL OPPORTUNITY Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. CANDIDATE PRIVACY I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: Москва GigaChat (GigaChain): Agentic Post-Training и Online RL Обязанности **Исследовать поведение модели:** * разбирать ошибки GigaChat в длительных задачах: потерю цели и контекста, слабое планирование, неверный выбор инструментов, зацикливание, ошибки восстановления и преждевременное завершение работы * анализировать отдельные шаги и целые траектории, находить систематические паттерны успешного и неуспешного поведения * понимать источник проблемы и определять, что нужно менять: обучающие данные, objective, reward-сигнал, модель или agentic environment. **Улучшать модель:** * разрабатывать и улучшать post-training пайплайны для агентных сценариев * работать с rollout’ами, reward-сигналами, rule-based и execution-based верификаторами, judge- и reward-моделями * создавать обучающие выборки из реальных и синтетических агентных траекторий, включая фильтрацию и отбор наиболее полезных примеров * выбирать подходящий метод обучения и понимать, когда сложный RL-контур оправдан, а когда задачу эффективнее решить более простым способом. **Оценивать изменения:** * строить evaluation для многошаговых агентных задач и анализировать качество не только по финальному результату, но и по поведению модели внутри траектории * проверять, переносится ли улучшение между задачами, бенчмарками и харнесами * контролировать регрессии и воспроизводимость результатов * взаимодействовать с командами обучения, инференса, данных, API и агентных харнесов. Требования * сильное владение Python и практический опыт работы с PyTorch * практический опыт LLM post-training: SFT, preference optimization, RLHF, online RL или близкие направления * умение самостоятельно ставить ML-гипотезы, проектировать эксперименты и делать выводы по их результатам * опыт построения пайплайнов данных * навык анализа модели на уровне отдельных примеров и траекторий * способность доводить исследовательскую идею до работающего и воспроизводимого решения. Условия * возможность выбрать удобный формат работы: гибрид или офис * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * ипотека выгоднее до 7% для каждого сотрудника * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

• Опыт от 5 лет в Quant / ML / DS. • Сильная математическая база.