Вакансии

Location: Paris; Zurich; Warsaw; 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. ABOUT THE RESEARCH ENGINEERING TEAM   The team spans Platform (shared infra & clean code) and Embedded (inside research squads). Engineers can move along the research↔production spectrum as needs or interests evolve.   As a Research Engineer – ML track, you’ll build and optimise the large-scale learning systems that power our open-weight models. Working hand-in-hand with Research Scientists, you’ll either join:   - Platform RE Team: Enhance the shared training framework, data pipelines and cluster tooling used by every team; or - Embedded RE Team: Sit inside a research squad (Alignment, Pre-training, Multimodal, Safety …) and turn fresh ideas into repeatable, scalable code.     What You Will Do   • Accelerate researchers by taking on the heavy parts of large-scale ML pipelines and building robust tools. • Interface cutting-edge research with production: integrate checkpoints, streamline evaluation, and expose APIs. • Design, implement and benchmark ML algorithms; write clear, efficient code in Python. • Deliver prototypes that become production-grade components for Vibe and our enterprise API.   What We're Looking For   • Master’s or PhD in Computer Science (or equivalent proven track record). • 4 + years working on large-scale ML codebases. • Hands-on with PyTorch, JAX or TensorFlow; comfortable with distributed training (DeepSpeed / FSDP / SLURM / K8s). • Experience in deep learning, NLP or LLMs; bonus for CUDA or data-pipeline chops. • Strong software-design instincts: testing, code review, CI/CD. • Self-starter, low-ego, collaborative.   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.

Задачи: — разработка, тестирование и внедрение ИИ-агентов (в том числе LLM-as-a-Judge) и классических ML-моделей для оценки качества, детекции аномалий, прогнозирования деградации и автоматической локализации причин сбоев — исследование и внедрение новых подходов в области настройки LLM, LLM-as-a-Judge и RAG, чтобы сделать мониторинг точнее, стабильнее и понятнее — ведение проекта по полному циклу: от идеи и прототипа до рабочего решения в проде, его тестирования и поддержки — проектирование пайплайнов для работы с данными (трейсами агентов) и обучения моделей, интегрируя их в нашу MLOps экосистему — взаимодействие с командами разработки и валидации ИИ-агентов, MLOps для интеграции решений и формирования лучших практик. Требования: — глубокое знание математической статистики, алгоритмов классического ML и архитектур нейросетей — опыт работы от 5 лет в роли Data Science / Machine Learning с полным циклом разработки — от исследований и прототипирования до внедрения в прод и мониторинга — опыт проведения аналитических исследований (R&D): умение самостоятельно изучать проблемную область, формулировать и проверять гипотезы, выбирать и адаптировать state-of-the-art методы под задачи проекта — уверенное владение стеком технологий для анализа, экспериментов и разработки: NumPy, Pandas, Polars, Scikit-learn, XGBoost, LightGBM, CatBoostOptuna / Hyperopt — навык написание чистого, модульного кода на Python, понимание принципов SOLID, опыт работы с Git. Будет преимуществом: — опыт разработки ИИ-агентов / агентных систем, понимание принципов их работы, коммуникации и оркестрации — опыт работы с трейсами и метаданными ИИ-агентов (OpenAI, Arize Phoenix, LangSmith) — опыт работы с векторными базами данных — знание observability-стека (OpenTelemetry, Prometheus, Grafana) для мониторинга ML-систем — публикации или значимый вклад в open-source в области ML/NLP/LLM. Условия: — комфортный современный офис: г. Москва, метро Кутузовский пр. — формат работы– офис, по согласованию с руководителем возможно выполнение пула задач в гибридном формате — ежегодный пересмотр зарплаты, годовая премия — корпоративный спортзал и зоны отдыха — более 400 образовательных программ СберУниверситета для профессионального и карьерного развития — программа адаптации и помощь руководителя на старте — расширенный ДМС (медицинское страхование), льготное страхование для семьи — ипотека для сотрудников — бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров — вознаграждение за рекомендацию друзей в команду Сбера.

Location: San Francisco Bay Area, USA Workplace: Hybrid Why work at Higgsfield AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. About the role: We are looking for an Investor Relations Manager, Capital Markets & Strategic Research to build and deepen Higgsfield’s relationships across investment banks, equity research, institutional investors, and the broader capital markets ecosystem. This is not a traditional IR role focused on quarterly earnings, filings, or maintaining an investor database. As a private, fast-growing AI company, our goal is to establish Higgsfield as a primary source of insight for the financial community on Creative AI and the transformation of the broader creative economy. You will build relationships with the analysts, bankers, and investors shaping how emerging technology categories are understood, helping ensure they have the data, context, and access needed to understand the size of the market and Higgsfield’s position within it. The goal is not paid placement. It is to build the relationships and credibility that lead analysts to independently recognize Higgsfield as one of the companies defining the Creative AI category. What you'll do: - Build and manage relationships with investment bankers, equity and thematic research analysts, institutional and private-market investors, hedge funds, and other influential members of the capital markets ecosystem. - Establish a systematic engagement program with research teams at leading investment banks. - Develop a regular cadence of analyst briefings, executive conversations, and relationship-building across Wall Street. - Track relevant research covering Creative AI, generative video, the creator economy, advertising, media, AI infrastructure, and adjacent markets. - Make Higgsfield a trusted resource for analysts by providing market intelligence, data, executive access, and informed perspectives on how AI is transforming creative industries. - Educate analysts and bankers on the size and structure of the Creative AI opportunity and why the relevant TAM extends across multiple large existing industries. - Identify upcoming sector reports and research initiatives where Higgsfield can provide insight and contribute to the underlying investment thesis. - Create opportunities for earned inclusion of Higgsfield in thematic and sector research. - Identify opportunities to collaborate on or co-commission credible research examining Creative AI and the transformation of the creative economy, while maintaining a clear distinction between sponsored research and independent analyst coverage. - Partner with Higgsfield leadership, communications, and finance to develop the data, market frameworks, benchmarks, and narratives needed to explain the category. - Track analyst and banking relationships, engagements, relevant reports, upcoming research themes, and resulting outcomes. - Build a deliberate strategy for converting relationships into tangible outcomes rather than treating relationship-building itself as the objective. Requirements: - 3–6+ years of experience in investor relations, investment banking, equity research, capital markets communications, strategic financial communications, or a closely related field. - Strong understanding of how Wall Street research is produced and how relationships with analysts and investment banks are built. - Ability to discuss TAM, industry structure, competitive positioning, and technological disruption with sophisticated financial audiences. - Ability to translate a fast-moving technology story into a credible capital markets thesis without turning it into marketing language. - Highly relationship-driven while remaining focused on measurable outcomes. - Strong written and verbal communication skills with the ability to work closely with senior executives and cross-functional teams. - Comfortable operating in a fast-moving environment where the category, company, and market narrative are evolving quickly. *Nice to have: - Existing relationships across investment banks, equity research analysts, institutional investors, or the broader capital markets community. - Experience covering or working within AI, technology, internet, media, advertising, the creator economy, or high-growth private technology companies. - Experience working with thematic or sector research and understanding how emerging technology categories become incorporated into broader investment theses. - Experience helping position a private, high-growth company with sophisticated financial audiences. Compensation & Benefits - We offer a competitive and thoughtfully structured compensation package designed to align with impact, experience, and long-term growth. - Base Salary: The anticipated salary range for this role is $175,000 - $240,000, depending on experience, skills, scope, and location. - Bonus: This role is Bonus eligible and may participate in the Company's discretionary annual bonus program. - Equity: In addition to cash compensation, employees are eligible to participate in the company’s stock option program and share in Higgsfield’s long-term growth. - Benefits: We offer a comprehensive benefits package designed to support employees professionally and personally, including medical, dental, and vision insurance, a competitive 401(k) retirement plan with company matching, and additional benefits and perks. - The opportunity to work on ambitious AI products alongside a highly experienced, fast-moving, and international team. - Significant ownership, direct impact, and opportunities for professional growth as the company scales. This is a hybrid role based in the San Francisco Bay Area. Team members are expected to work from our San Francisco office three full days per week, with the remaining days worked remotely and are expected to be available during agreed working hours and to maintain sufficient overlap with the relevant team’s time zone. We value in-person collaboration, active communication, responsiveness, and close partnership across teams. Higgsfield AI is an equal opportunity employer. We are committed to building a diverse and inclusive team and do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic.

Задачи: — искать специалистов на международном рынке: США, Канада, Австралия, UK, Европа — работать с LinkedIn, Google / X-Ray Search, Boolean Search, профессиональными сообществами и базами — самостоятельно формировать поисковые запросы, target-листы компаний и стратегию поиска — работать с разными направлениями: FinTech, Payments, Product, AI / ML, SaaS, Consumer Tech, Business Требования: — опыт в роли Talent Sourcer / Researcher / Analyst от 1 года — уверенная работа с LinkedIn, желательно наличие прогретого аккаунта — владение Boolean Search и X-Ray Search — английский B2+ для работы с англоязычными профилями и письменной коммуникации Будет плюсом: — опыт в FinTech / Payments / Banking / SaaS / Consumer Tech Условия: — фикс от 700$ + KPI + бонусы — формат: fulltime, remote

Location: Paris Workplace: Hybrid 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 Cybersecurity is one of the areas where AI could do the most good — and one where the capability must be built with particular care. As a Research Engineer on this track, you'll push our models' capabilities in vulnerability discovery and remediation, security analysis, incident response, and across the offensive-to-defensive spectrum of cybersecurity, and it will be your job to develop that ability deliberately and safely. The work sits at the meeting point of research and engineering: you'll devise new approaches and be the one to implement them. Concretely, that means designing and building RL environments that reproduce realistic security scenarios, pipelines that generate synthetic training instances at scale, and experiments and evaluations that show what our models can actually do. Your results feed directly into the production training runs that shape our frontier models, in close collaboration with Mistral's researchers, engineers, and security specialists. Security specialists and ML engineers are both welcome here — what matters is that you can hold your own in both worlds, and are eager to go deeper on the one you know less. WHAT YOU WILL DO - Design and implement RL environments simulating cybersecurity scenarios. - Build the pipelines and infrastructure that generate synthetic cybersecurity training instances at scale — thousands of scenarios, not one hand-crafted exercise. - Conduct experiments and evaluations of model capabilities on these environments, from quick prototypes to controlled benchmark runs. - Own the infrastructure behind the environments: containers, sandboxes, VMs, cloud deployments, and orchestration (Kubernetes), all managed as code. - Partner with researchers and security specialists across Mistral, distilling their domain expertise into reproducible environments and datasets. - Write clear, efficient code in Python and enforce strong software-design practices: testing, code review, CI/CD. WHAT WE'RE LOOKING FOR - Hands-on expertise in offensive and/or defensive cybersecurity: vulnerability analysis, web/network/cloud security, secure coding practices, and SOC. - Strong software engineering skills: clean, reliable, well-tested code — not just exploit scripts. - Fluency in Python plus comfort reading lower-level languages (C/C++) for vulnerability analysis. - DevOps experience: Docker, Kubernetes, cloud deployments, sandboxed or simulated environments. - A pragmatic research-to-engineering mindset: ship a working first version, then refine and scale it. - Working knowledge of RL techniques and LLM training methodologies, or strong motivation to develop it. - Self-starter, low-ego, collaborative — comfortable working across research and engineering. NICE-TO-HAVES - CTF, cyber-range, or bug-bounty experience — as a player, challenge author, or platform builder. - A research background in cybersecurity, academic or industrial, or in another experimental discipline. - Prior experience building RL environments or large-scale ML training infrastructure. - Relevant open-source contributions and projects. 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: Singapore 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. ABOUT THE JOB Mistral AI is seeking Applied Scientists and Research Engineers focused on robotics. You will design, train, and deploy SOTA robotics models (VLM, VLA models for navigation and manipulation) and apply them to diverse use cases. You'll work cross-functionally with internal and external science, engineering, and product teams to deliver high-impact AI solutions. WHAT YOU WILL DO - Run pre-training, post-training and deploy state of the art models on large clusters. - Generate and curate datasets (image-text, video-text), and build evaluators/benchmarks for perception, navigation and manipulation tasks. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases. - Manage research projects and communications with client research teams. ABOUT YOU - Fluent in English with excellent communication skills. - Expert with PyTorch or JAX. - Experience with Vision Language Models (VLM), Vision-Language-Action (VLA) models, perception, navigation and manipulation, simulation tools (e.g. Isaac SIM). - Clean, readable, high-performance Python code. - Doesn't need roadmaps. Ships. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. NICE TO HAVE - PhD / Master in a relevant field (Robotics, Machine Learning). - Research experience in robotics navigation, perception, manipulation. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. 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: Berlin Workplace: Hybrid adjoe builds the technologies behind mobile app growth and monetization, challenging the status quo of adtech by redefining how apps acquire users and generate revenue. Our two products, Playtime Arcade and adjoe Ads, sit at opposite ends of the mobile advertising spectrum: rewarded engagement and programmatic in-app advertising. Together they run on 13% of the world's smartphones, connecting advertisers, publishers, and hundreds of millions of users, with one goal: making mobile advertising work better for everyone in the ecosystem. Next-Gen Machine Intelligence for Scalable Discovery & Engagement The Data Science Research team builds foundational ML representations and advanced AI capabilities that enhance both Playtime and adjoe Ads. Operating as a horizontal deep-tech layer, the team leverages advanced AI and deep learning approaches—specifically generative approaches —to deliver critical systems such as high-dimensional user embeddings, general content understanding and sequential recommendation. These frameworks scale adjoe's products beyond standard industry limitations, utilizing behavioral and transactional data from over 770 million users. The team operates at the intersection of bleeding-edge R&D and high-scale production engineering, acting as the company’s internal science bar raiser and primary consulting layer for complex ML bottlenecks. The stack is optimized for deep learning and heavy data throughput: PyTorch and [Ray/Hugging Face] for training and fine-tuning foundation models, Trino and Athena for querying massive user-behavior data lakes, and dedicated GPU infrastructure for heavy workloads. The full lifecycle of these AI capabilities is owned by the team—from academic paper translation and offline prototyping to deploying core algorithmic frameworks built to sustain high-throughput, realtime production environments. Your Mission & Who We Are Looking For: - PhD or equivalent research depth, with a production track record. You have a PhD in CS, Statistics, Math, or Physics, or an MSc with extensive industry research, and publications in top-tier venues like SIGIR, KDD, NeurIPS, or ICLR. You've spent 4+ years building large-scale recommender systems in high-throughput environments: AdTech, e-commerce, or social. - You translate research into production, not just prototypes. You distill SOTA research into robust, production-ready code optimized for sub-millisecond latency. At adjoe, that means architecting multi-stage recommendation pipelines, Generative Retrieval, Deep Ranking, and Re-ranking, serving millions of requests across a stack built on 770 million users' behavioral data. - Deep expertise in PyTorch and large-scale model optimization. You have hands-on experience with high-concurrency optimization, model quantization, and distillation, the engineering side of getting large generative models to run under extreme production constraints, not just in research environments. - Content understanding and embeddings are core to your work. You research and develop information-rich user and ad embeddings using unsupervised and generative approaches, directly improving the quality of predictions across both Playtime and adjoe Ads. - Raises the technical bar around them. You lead architectural debates, mentor junior scientists, and drive the team's research direction without needing a roadmap handed to you. 🌎 We welcome applications from talent worldwide and provide relocation support to Hamburg, Germany for those ready to join our team. What’s in It for You? At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day. - Go Big. Own projects with impact on 770M users and push adtech boundaries. - Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum. - Be Direct. Solve problems openly and collaborate across teams. - Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other. - Have Fun. Celebrate wins, enjoy daily victories, and bring your energy. We welcome applications from people who will contribute to the diversity of our company.

Задачи: — искать специалистов на международном рынке: США, Канада, Австралия, UK, Европа — работать с Google / X-Ray Search, Boolean Search, профессиональными сообществами и базами — самостоятельно формировать поисковые запросы, target-листы компаний и стратегию поиска — анализировать эффективность каналов и outreach, тестировать новые подходы к сорсингу — работать с разными направлениями: FinTech, Payments, Product, AI / ML, SaaS, Consumer Tech, Business Требования: — опыт в роли Sourcer / Talent Sourcer / Researcher / Recruiter / Analyst от 1 года — уверенная работа с Boolean Search, желательно наличие прогретого аккаунта — хорошее владение Boolean Search и X-Ray Search — опыт cold sourcing — английский B2+ для работы с англоязычными профилями и письменной коммуникации Условия: — удаленная работа — график 5/2 — от 700$ + KPI + бонусы

Location: South Africa About the role We're a global education company running live, expert-led business courses across multiple markets. As we grow, so does the volume of legal questions that come with operating in many jurisdictions at once — how we contract with instructors in different countries, how we structure entities, how we respond when a regulator asks a question. We're hiring a dedicated legal role to take ownership of the research, analysis, and drafting that sits underneath those decisions. This is a genuinely broad role for someone early in their legal career who wants exposure to real cross-border commercial and employment questions, rather than a narrow slice of one. You'll research law in jurisdictions you haven't worked in before — the US, the UK and EU, South Africa, Australia, and across APAC — and your job will be to bring back a clear answer, not a hedge. What you'll do Research legal questions across multiple jurisdictions as we expand — contractor and partner engagement models, entity structuring, employment and commercial law, etc. Draft and maintain our contract templates: consulting agreements, teaching assistant agreements, statements of work, amendments, and termination agreements, with jurisdiction-specific variants Redline counterparty contracts and flag the terms that actually matter Build and own our legal register: active matters, deadlines, obligations, renewals, filings Scope and brief external counsel — write the question, assemble the pack, track cost and turnaround, and pressure-test what comes back Support entity formation, restructuring, and market-entry diligence Maintain approved communication templates and FAQs for teams who work with our instructors Build the systems that let a small legal function support a fast-growing company Requirements A law degree and 2–4 years of practical legal experience — private practice, in-house, or legal services Excellent written English. The core output of this role is a one-page memo a non-lawyer can act on immediately. Clarity beats comprehensiveness. Proven legal research skill, including in legal systems that aren't your own — and the judgment to know when a question needs local counsel and how to frame it for them Contract drafting and redlining experience Thoughtful, verified use of AI research tools. We use them; we also check every citation at source. Comfort with ambiguity, and the initiative to turn a half-formed business question into a precise legal one Interest in how the business actually works, not just the legal question in isolation Nice to have Experience with cross-border contractor or freelancer engagement models Employment or labour law background Admission to the bar in your home jurisdiction Data protection experience (GDPR, POPIA) Experience in a distributed, remote-first company Benefits Competitive Compensation: Competitive salary,Opportunities for career advancement as ELVTR continues to grow globally Learn and Grow: Free access to ELVTR courses,Ongoing professional development opportunities,Career growth within one of the world's fastest-growing online education companies Remote-First Culture : Work from wherever you're most productive, Flexible and supportive work environment,Collaborative international team Health & Wellbeing: Gym membership reimbursement,Mental health support, Generous paid vacation allowance Why Join ELVTR? Make an Impact: Every course you help create empowers professionals to build new skills, advance their careers, and unlock opportunities they never thought possible. Grow Your Career: We're committed to developing our people. As ELVTR continues to expand globally, you'll have opportunities to grow professionally, take on new challenges, and shape the future of online education. Join a Winning Team :Work alongside passionate educators, creators, marketers, and innovators who are committed to delivering world-class learning experiences and making education more accessible around the world. Ready to Help Shape the Future of Online Learning? Submit your CV and a short note on a legal question you researched where the answer wasn't obvious — what you found, and what you recommended.

Location: Ukraine About the role We're a global education company running live, expert-led business courses across multiple markets. As we grow, so does the volume of legal questions that come with operating in many jurisdictions at once — how we contract with instructors in different countries, how we structure entities, how we respond when a regulator asks a question. We're hiring a dedicated legal role to take ownership of the research, analysis, and drafting that sits underneath those decisions. This is a genuinely broad role for someone early in their legal career who wants exposure to real cross-border commercial and employment questions, rather than a narrow slice of one. You'll research law in jurisdictions you haven't worked in before — the US, the UK and EU, South Africa, Australia, and across APAC — and your job will be to bring back a clear answer, not a hedge. What you'll do Research legal questions across multiple jurisdictions as we expand — contractor and partner engagement models, entity structuring, employment and commercial law, etc. Draft and maintain our contract templates: consulting agreements, teaching assistant agreements, statements of work, amendments, and termination agreements, with jurisdiction-specific variants Redline counterparty contracts and flag the terms that actually matter Build and own our legal register: active matters, deadlines, obligations, renewals, filings Scope and brief external counsel — write the question, assemble the pack, track cost and turnaround, and pressure-test what comes back Support entity formation, restructuring, and market-entry diligence Maintain approved communication templates and FAQs for teams who work with our instructors Build the systems that let a small legal function support a fast-growing company Requirements A law degree and 2–4 years of practical legal experience — private practice, in-house, or legal services Excellent written English. The core output of this role is a one-page memo a non-lawyer can act on immediately. Clarity beats comprehensiveness. Proven legal research skill, including in legal systems that aren't your own — and the judgment to know when a question needs local counsel and how to frame it for them Contract drafting and redlining experience Thoughtful, verified use of AI research tools. We use them; we also check every citation at source. Comfort with ambiguity, and the initiative to turn a half-formed business question into a precise legal one Interest in how the business actually works, not just the legal question in isolation Nice to have Experience with cross-border contractor or freelancer engagement models Employment or labour law background Admission to the bar in your home jurisdiction Data protection experience (GDPR, POPIA) Experience in a distributed, remote-first company Benefits Competitive Compensation: Competitive salary,Opportunities for career advancement as ELVTR continues to grow globally Learn and Grow: Free access to ELVTR courses,Ongoing professional development opportunities,Career growth within one of the world's fastest-growing online education companies Remote-First Culture : Work from wherever you're most productive, Flexible and supportive work environment,Collaborative international team Health & Wellbeing: Gym membership reimbursement,Mental health support, Generous paid vacation allowance Why Join ELVTR? Make an Impact: Every course you help create empowers professionals to build new skills, advance their careers, and unlock opportunities they never thought possible. Grow Your Career: We're committed to developing our people. As ELVTR continues to expand globally, you'll have opportunities to grow professionally, take on new challenges, and shape the future of online education. Join a Winning Team :Work alongside passionate educators, creators, marketers, and innovators who are committed to delivering world-class learning experiences and making education more accessible around the world. Ready to Help Shape the Future of Online Learning? Submit your CV and a short note on a legal question you researched where the answer wasn't obvious — what you found, and what you recommended.

Location: United States About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . The Role Turing builds large-scale datasets and reinforcement learning (RL) environments that power post-training for the world’s leading AI labs and enterprises. We create RL environments to evaluate and improve our customers' models on complex, long-range, multi-step workflows across high-GDP-value domains such as Finance, Sales, Retail, Developer Tools, Collaboration, Customer Experience. The environments vary depending on the model capability being evaluated / improved, a few examples of environment types are listed here: Environments for Software Engineering / coding agents UI-Environments for Computer-Use/Browser-Use agents MCP-based Environments for general function-calling agents across various enterprise and consumer applications We are seeking Research Engineers to advance our understanding of frontier AI systems and develop practical innovations in data, algorithms, evaluation, and training. You will work at the intersection of research and engineering, investigating high-impact questions that improve real-world AI systems. You will design and run rigorous experiments, develop research-grade prototypes and tooling, and collaborate with Research, Engineering, Product, and Operations teams to translate promising ideas into scalable applications. This role offers the opportunity to contribute to both foundational research and applied AI development across synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. What You’ll Do 1. Conduct Research on Frontier AI Systems Investigate the capabilities, limitations, and training methods of frontier AI systems. Formulate research questions that can inform Turing’s products, platforms, and technical strategy. Explore new approaches to synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation. Stay current with advances in machine learning and identify opportunities for meaningful technical contribution. 2. Build and Evaluate Research Systems Develop research-grade datasets, experiments, prototypes, tooling, and evaluation frameworks. Train, test, and evaluate models using modern AI and machine learning tools. Analyze results carefully and draw clear, evidence-based conclusions. Establish sound practices for experimental rigor, data quality, reproducibility, and interpretation. Iterate quickly from early hypothesis through validated technical insight. 3. Translate Research into Practical Impact Collaborate closely with Research, Engineering, Product, and Operations teams. Translate research findings into improvements for Turing’s products, platforms, and AI capabilities. Help identify which ideas are ready to move from exploration into scalable, real-world applications. Communicate technical findings clearly to both specialized and cross-functional audiences. 4. Contribute to the Research Community Share findings through technical reports, publications, open-source work, workshops, or conference participation where appropriate. Contribute to Turing’s research culture through technical discussions, peer review, mentorship, and collaboration. Represent Turing thoughtfully within the broader AI research community. What We’re Looking For Research background: PhD or Master’s degree in artificial intelligence, machine learning, computer science, or a closely related technical field; exceptional equivalent research experience will also be considered. Technical depth: Strong foundation in machine learning and practical experience designing experiments, training or evaluating models, and working with modern AI tooling. Relevant expertise: Demonstrated research experience in synthetic or agentic data generation, reinforcement learning or post-training, AI understanding, evaluation, or benchmarks. Research engineering ability: Strong programming skills and the ability to implement, test, and iterate quickly in a research environment. Scientific judgment: Sound judgment around experimental rigor, data quality, reproducibility, and evidence-based decision-making. Communication and collaboration: Clear written and verbal communication skills, intellectual curiosity, and the ability to work effectively across research and engineering teams. A note from our CTO, Ece Kamar Some of the most important questions in AI can't be answered from inside a single lab: how to evaluate frontier models, how data and RL truly drive capability, and what happens when AI meets the real world. At Turing, we work directly with frontier labs, the academic community, and enterprises deploying AI at scale. That creates a feedback loop where deployment shapes our research and our research shapes the field, and we publish our findings, datasets, and benchmarks openly. Join our talented team at Turing to push the frontier of AI with rigorous science that matters. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training and RL environment design. Build datasets and environments that directly improve the capabilities of advanced AI systems. Help advance coding agents’ ability to understand, plan, and execute complex software-engineering tasks. Apply frontier AI innovations to high-value enterprise workflows. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. Compensation: $250,000 to $400,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: United States About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . The Role Turing is seeking exceptional AI Research Scientists to join our STEM research organization and develop new ways to evaluate, train, and improve frontier AI systems. This is a research-first role focused on problems where the right benchmark, dataset, or methodology often does not yet exist. You will identify important gaps in the literature, propose ambitious new research directions, and take projects from initial hypothesis through experimentation, benchmark construction, and publication. Our research is deliberately focused on frontier STEM evaluation, synthetic data, hallucination and reliability, and agentic science . We are looking for scientists who can recognize important problems early, formulate them precisely, and design rigorous research programs to answer them. What You'll Do Frontier benchmarks and evaluation Identify high-impact gaps in existing benchmark and evaluation literature. Design novel benchmarks in and across STEM fields and on general model functionality. Develop evaluations for emerging model capabilities that are poorly captured by traditional static benchmarks. Design rigorous task-generation, grading, contamination-control, difficulty-calibration, and validation methodologies. Build benchmarks that can become both valuable research contributions and meaningful standards for evaluating frontier models. Synthetic data and post-training Develop methods for generating high-quality synthetic STEM training data. Study how task selection, difficulty, diversity, verification, filtering, and data quality affect downstream performance. Explore methods for generating useful training signal in domains where expert human data is scarce or expensive. Design experiments that determine when synthetic data genuinely improves capabilities rather than simply increasing training volume. Hallucination, reliability, and verification Study hallucination, uncertainty, calibration, and epistemic failure in technical domains. Develop evaluations and methods for improving factual reliability, self-correction, verification, citation, and appropriate abstention. Investigate when models should reason internally, invoke tools, seek external evidence, or recognize that they do not know. Agentic science Research AI systems capable of performing extended scientific and technical work. Develop workflows involving literature search, coding, simulation, tool use, experimentation, verification, and iterative reasoning. Evaluate long-horizon scientific agents and identify the bottlenecks preventing them from reliably performing real research. Explore new approaches to human-AI and multi-agent scientific collaboration. New research directions The areas above are our core focus, not an exhaustive list. Researchers will also have significant latitude to propose new programs in areas such as reasoning, model evaluation, AI-for-science, data generation, and emerging capabilities. What We’re Looking For PhD or equivalent research experience in machine learning, computer science, mathematics, physics, chemistry, biology, engineering, statistics, or another highly technical field . Demonstrated ability to formulate and execute original research. Strong understanding of modern LLMs and the frontier AI research landscape. Excellent experimental design, quantitative reasoning, and scientific judgment. Ability to rapidly understand unfamiliar technical literature and develop expertise in new areas. Strong Python skills and the ability to independently build research prototypes and evaluation pipelines. Excellent technical writing and communication. Comfort working in a fast-moving environment where the research agenda evolves with the frontier. A strong publication record is valuable, but we care most about whether you can identify important questions, design rigorous ways to answer them, and execute quickly enough for the results to matter . A note from our CTO, Ece Kamar Some of the most important questions in AI can't be answered from inside a single lab: how to evaluate frontier models, how data and RL truly drive capability, and what happens when AI meets the real world. At Turing, we work directly with frontier labs, the academic community, and enterprises deploying AI at scale. That creates a feedback loop where deployment shapes our research and our research shapes the field, and we publish our findings, datasets, and benchmarks openly. Join our talented team at Turing to push the frontier of AI with rigorous science that matters. Why Turing Work directly with leading AI labs and enterprises at the frontier of post-training and RL environment design. Build datasets and environments that directly improve the capabilities of advanced AI systems. Help advance coding agents’ ability to understand, plan, and execute complex software-engineering tasks. Apply frontier AI innovations to high-value enterprise workflows. Operate with high autonomy, rapid iteration, and meaningful commercial impact. Collaborate with exceptional colleagues from organizations including Google, Meta, Amazon, and other leading technology companies. Contribute to research that may be shared through technical publications and leading conferences such as ICLR, ICML, and NeurIPS. Compensation: $150,000 to $300,000 OTE + Equity Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Задачи: · Ежедневно исследовать TikTok, Instagram Reels и YouTube Shorts по заданным категориям, регионам, хештегам и креаторам; · Проводить первичный скрининг ориентировочно 80-120 роликов в день; · Отбирать перспективные ролики для глубокого анализа; · Анализировать просмотры, вовлеченность, динамику, показатели аккаунта и внутренний коэффициент виральности; · Проверять ролики по внутреннему чек-листу на релевантность и воспроизводимость механики; · Корректно заносить результаты в рабочую таблицу; · Передавать лучшие находки менеджеру на подтверждение; · Формировать базу успешных креаторов, хуков, форматов и повторяющихся механик; · Собирать и актуализировать данные по результативности креаторов. Требования: · Опыт в сходных задачах в роли Marketing Analyst / Influence Marketing Specialist от 1-2 лет; · Высокая внимательность к цифрам и деталям; · Уверенная работа с Google Sheets / Excel: фильтры, сортировка, базовые формулы, большие таблицы; · Хорошее понимание TikTok / Reels / Shorts; · Способность аргументировать выбор данными и критериями, а не только субъективным мнением; · Готовность работать с большим объемом однотипной информации; · Аналитическое мышление, системность, дисциплина и самостоятельность; · Готовность к ежедневной research-работе. Будет плюсом: · Опыт анализа short-form контента; · Понимание performance-маркетинга и контент-метрик; · Опыт работы с VidIQ, SocialBlade или аналогами; · Английский язык от Intermediate; · Понимание US/EU digital-контекста, трендов и мемов; · Опыт research-задач или работы с большими массивами данных. Условия: · Официальное трудоустройство; · Пятидневная рабочая неделя с гибридным форматом работы; · Быстрый и понятный процесс найма — оперативно проводим собеседования и даем обратную связь; · Работа с современным англоязычным контентом; · Постоянный поток задач и возможность расти внутри команды; · Открытый стиль управления без микроменеджмента — доверяем профессионализму и инициативе; · Обсуждение идей на равных — не боимся экспериментировать и вместе радуемся результатам.

В роли контент-аналитика предстоит заниматься исследованием и анализом контента, выявлением тенденций и подготовкой отчетов на основе собранных данных. Кандидат должен обладать навыками работы с аналитическими инструментами и уметь систематизировать информацию для принятия решений. Дополнительным преимуществом станет опыт в смежных областях и знание современных технологий анализа данных. В рамках работы ожидается взаимодействие с командой для улучшения качества контента и поддержки стратегических инициатив компании.

Location: United States (Remote) Workplace: Remote ABOUT ONEPAY OnePay is the consumer fintech trusted by millions of Americans to make money better. Our financial system is broken. High fees, low rates, and too few ways to actually grow your money. We’re fixing it. And we’re moving fast. We’re an all-in-one financial services platform that brings together banking, high-yield savings, credit cards, point-of-sale lending, investing, and crypto in one place. We also partner with employers, HCM providers, gig platforms, and others to deliver embedded financial services to millions of employees and frontline workers. We’re backed by Walmart, the world’s largest retailer, and Ribbit Capital, one of fintech’s most respected investors, giving us rare scale, distribution, and the opportunity to build something truly category-defining. But what really sets OnePay apart is how we move. Our customers don’t have time to wait… and neither do we. This place moves fast, and we’re looking for people who are: - Ready to run - Hungry and driven by urgency - Exceptional at what they do, with low ego - Comfortable operating in motion THE ROLE As an AI Research Intern, your mandate is to research and prototype foundation models, both transformer-based and graph-based, applied to OnePay's customer, transaction, and merchant data. You'll work on real modeling problems and build a working prototype that demonstrates the approach. This role will impact OnePay's vision by providing a remarkable customer experience, driving positive business outcomes, and improving operational efficiency. You will work closely with the product, engineering and applied science team(s) working across all business units. This role reports to the Head of AI/ML. This role is responsible for: - Research, design, and train foundation models on OnePay's data, working with transformer and/or graph-based architectures. - Run experiments, evaluate results rigorously, and turn promising findings into a working prototype. - Opportunity to work in an extremely fast paced growing company - Partner with Product, Engineering and Analytics teams to ensure we are providing a remarkable customer experience. - Driving significant impact on the company’s bottom line. YOU BRING - Final-Year Graduate Student: You’re in the final year of a master’s or PhD program, expected to graduate in Fall 2027 or Spring 2028, majoring in Engineering or a related field. - Deep Learning Fundamentals: You have a strong grasp of how neural networks work under the hood, including backpropagation, attention, embeddings, optimization, and training dynamics. You've implemented, trained, or fine-tuned models yourself through research, coursework, or personal projects, and you're comfortable working in PyTorch or an equivalent framework. - Prior Experience: You've completed at least one previous internship in research, machine learning, or software engineering, or have built substantial personal or academic projects you're excited to talk through. - Availability: This is a full-time, 8-week program running June 21 - August 13, 2027. You are available to work in our New York City office at least 3-4 days a week throughout. - Proactive & Collaborative Attitude: You have an act-like-an-owner mentality, thrive in a fast-moving environment, and enjoy working with others to achieve collective goals. - Critical Thinking & Problem-Solving Skills: You enjoy tackling complex challenges, analyzing problems, and developing solutions. Clear communication of ideas is one of your strengths. - Organized & Detail-Oriented: You’re a keen listener with strong organizational skills, capable of managing multiple tasks efficiently. - Excited to Learn & Grow: You are passionate about being part of a rapidly growing start-up and look forward to expanding your skills in a real-world setting. NICE TO HAVE - Familiarity with transformer-based foundation model architectures, including pre-training, fine-tuning, inference, and the tradeoffs between approaches. - Exposure to graph-based learning or graph foundation models, such as GNNs, message passing, or representation learning on graph-structured data. - Coursework or projects involving Large Language Models or Generative AI. - Research output in any of the above: publications, workshop papers, or open-source contributions. WHAT WE OFFER - Early access to a high potential, high growth fintech - Hands on experience building product ready to ship - Beautiful NYC SoHo Office - Professional development and team social outings PROGRAM & APPLICATION TIMELINE - Program runs June 21 - August 13, 2027 (8 weeks, full-time, in our NYC office) - We review applications and conduct interviews on a rolling basis as they come in - No offer decisions will be made until the application window closes – all candidates are evaluated together before final decisions go out - We are targeting a finalized cohort by December 1, 2026 - If there are intern spots still available, we may reopen applications in Spring 2027 Work Authorization: OnePay will not sponsor applicants who need employment sponsored visas for this position. Future sponsorship will not be considered. STANDARD INTERVIEW PROCESS Our process varies by role. Most candidates go through: - AI-assisted initial screen - Interview with Talent Partner - Technical or Hiring Manager Interview - Team Interview - Executive Interview - Offer! EQUAL EMPLOYMENT OPPORTUNITY To build technology and products that are used and loved by people and solve real-world problems, we need to build a team with many different perspectives and experiences. We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We encourage candidates from all backgrounds to apply. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us at talent@onepay.com.

Location: Berlin Workplace: Hybrid ABOUT US: At Upvest, we are on a mission to make investing as easy as spending money. Upvest empowers businesses to offer a wide range of investment products and the best experience in the field of capital market investment and retirement planning. Upvest’s Investment API is easy to integrate so that fintechs and financial institutions can save resources and fully focus on their core business. We are proud to partner with Europe’s leading Fintechs and financial institutions such as DKB, Revolut, N26 and Raisin. Founded in 2017 by Martin Kassing, Upvest now brings together over 270 talented professionals from more than 70 nationalities. Upvest is backed by €280M in total funding from world-class investors, including BlackRock, Tencent, Sapphire Ventures, and Bessemer Venture Partners, Earlybird, Notion Capital, and Motive. Our latest €105M funding round in March 2026 - led by Sapphire and Tencent - serves as a massive catalyst for our growth, allowing us to offer premier investment experience. ABOUT THE ROLE: The role is designed for law graduates who are pursuing a doctorate (Promotion) or preparing for the (Zweite) Juristische Prüfung and want hands-on in-house experience in a regulated investment firm alongside their academic work. You will work closely with our lawyers and take on increasing responsibility over time. WHAT YOU’LL DO: - Support our Legal Team on domestic and international projects, in particular by reviewing and preparing first drafts of cooperation agreements with clients and partners. - Research legal questions raised by our Product, Project Management and Sales teams and prepare concise memos, with a focus on financial services regulation (e.g. WpIG, MiFID II, DORA). - Conduct initial legal reviews and risk assessments of vendor agreements and summarise the key points for the responsible lawyer. - Help develop and maintain our standard contracts, templates, playbooks and other key legal documents essential to operations. - Maintain and structure our contract inventory (contract management database) to ensure completeness, compliance and clear ownership. - Collaborate closely with the Legal Team to automate, operationalise and improve internal processes, including with AI-based legal tech tools. - Monitor regulatory developments relevant to Upvest (e.g. Bafin, ESMA, EU legislation) and prepare short briefings for the team. WHAT YOU BRING: - A completed first German law degree (Erste Juristische Prüfung, LL.B. or LL.M). You are pursuing or planning a doctorate (Promotion) or are currently a Rechtsreferendar:in. - First practical experience (internships, Referendariat stations, student assistant or research assistant roles), ideally in an international and fast-paced environment, is a plus but not required. - A keen interest in financial services, capital markets or regulatory law – ideally reflected in your studies, dissertation topic or first practical experience. - Enthusiasm for an agile and proactive working culture. - Very good communication skills with fluency in business English and German (the working language of our international team is English). Strong intercultural awareness and enthusiasm for working in a global environment. - A team-oriented spirit, with a passion for cross-disciplinary collaboration. - Confident use of Google Workspace, MS Office and AI tools, and curiosity about legal tech. HOW WE UPVEST IN YOU: - Best-in-class AI tools: Every Upvenger has €20,000 per year to spend on the best AI tools available — so you're always working with the most powerful models and tooling on the market. - Impact-driven work: We’re building the infrastructure that will power the future of investing in Europe. It’s complex, ambitious, and meaningful. You’ll work with modern technologies and create something entirely new. No legacy systems, no limits. - Wellbeing: Recharge with 30 days of annual leave and maintain a healthy lifestyle with sports benefits. Access confidential professional coaching and enjoy the flexibility to work remotely abroad for up to 183 days a year. Recharge with UpRest, a one-month fully paid sabbatical after every 4 years of working at Upvest. - Development: Growth is in our DNA. Each Upvenger has access to a personal development budget and the freedom to decide how to use it. - Compensation and equity: We believe that all Upvengers contribute to our success and deserve a competitive, above-market salary and a participation in our employee equity program. - Team celebrations: Participate in company-wide events, such as UpFest, dinners, offsites and our Holiday party, to connect with colleagues and celebrate our achievements. - Inclusion: We’re committed to a culture where everyone belongs and thrives. Our Employee Resources Groups foster inclusion and connection, like Upfem for our female Upvengers, or UpVergent supporting neurodivergent Upvengers and allies. OUR VALUES: - Make it easy for others. We simplify the complex and act with the best intentions. - Own the outcome. We are proactive, fast and confident to get the job done, valuing progress over perfection. - Rise to the challenge. We aim high and push the boundaries. We stay curious, learn and celebrate our wins together. - Tell the story. We start with the Why to align on purpose. We are transparent and share knowledge to empower and inspire others. Upvest is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Location: Mumbai WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it. THE ROLE: Research is at the core of WorldQuant. Through rigorous exploration and unconstrained thinking about how to apply data to the financial markets, our researchers are in constant search of new Alphas. We strive to understand data in ways our competitors don’t believe is possible. Researchers at WorldQuant employ tested processes seeking to identify high-quality predictive signals that we believe are undiscovered by the wider market. These signals are mathematical expressions of data that are used as inputs in our quantitative models. WorldQuant is seeking an exceptional individual to join the firm as a Quantitative Researcher. The person must have a strong understanding of the investment research process to create computer-based models that seek to predict movements of global financial markets. While prior finance experience is not required, a successful candidate must possess a strong interest in learning about finance and global markets. Candidates will have a research scientist mind-set; be a self-starter, a creative and persevering deep thinker who is motivated by unsolved challenges. ITS IMPACT: As we pursue our goal of creating new Alphas, we need researchers who will lead us there. WorldQuant’s unique investment platform is a leader amongst its peers and the methodology we employ is cutting edge. We desire people who will help us in our relentless pursuit to succeed. WHAT YOU’LL BRING: Ph.D. or M.S. degree from a leading university in a quantitative or highly analytical field (e.g. – Electrical Engineering, Physics, Computer Science, Mathematics, Financial Engineering) Ranked in the top 10% of bachelor’s degree class Demonstrated ability to program in Python and C/C++ on a Unix/Linux platform Excellent problem solving abilities and judgment with a strong attention to detail Mature, thoughtful, with the ability to operate in a collaborative, team-oriented culture Strong English language skills; ability to communicate complex concepts in simple terms Open for all department with GPA score above 8.5 is required By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction. Copyright © 2025 WorldQuant, LLC. All Rights Reserved. WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.

42 — независимая AI research-лаборатория, создающая универсальные фундаментальные модели для прогнозирования и принятия решений в сложных, быстро меняющихся системах. Стек: Go, Rust, Kafka, Postgres, ClickHouse. Амстердам, Нидерланды. Помощь с переездом.