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Location: San Francisco Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW We are looking for a Lead Technical Recruiter to help build Harvey Labs, our AI research organization. You’ll partner closely with our Chief Research Officer and technical leadership to build the team from the ground up, initially focused on post-training talent across data and evaluations, infrastructure, and modeling and training. You’ll own searches end-to-end, develop talent strategies for highly specialized AI talent markets, and help define how we identify and attract exceptional technical talent as Harvey Labs scales. This is a hands-on role with significant ownership. You’ll operate in ambiguity, develop a strong point of view on the AI talent landscape, and serve as a trusted advisor to technical leadership. WHAT YOU'LL DO - Partner closely with our Chief Research Officer and Harvey Labs leadership to translate technical priorities into recruiting strategies - Own full-cycle recruiting across specialized AI/ML, research, and engineering roles - Build deep talent maps across leading AI companies, research labs, startups, academia, and open-source communities - Develop creative, high-touch sourcing and engagement strategies for exceptional talent, from experienced researchers to emerging new grads - Help leaders define new profiles, calibrate talent bars, and evolve search strategies based on market insights - Advise leadership on talent availability, competitive dynamics, compensation, and candidate motivations - Drive searches from initial market mapping through offer strategy, negotiation, and close - Use data and market intelligence to continuously improve our recruiting strategy - Help build scalable recruiting processes and raise the bar for technical recruiting across Harvey WHAT YOU HAVE - 7+ years of full-cycle technical recruiting experience in fast-paced, high-growth environments - Experience recruiting for technical AI research teams or similarly specialized technical roles - Strong aptitude for understanding complex technical domains and evaluating candidate qualifications - Exceptional sourcer who enjoys identifying hard-to-find talent across research labs, startups, academia, open source, and other nontraditional channels - Willing to take creative, white-glove approaches to engaging and closing exceptional talent - Trusted advisor who can build credibility with highly technical leaders and candidates - Comfortable with ambiguity and able to help shape searches when the profile isn't fully defined - Strong instincts for talent and a genuine interest in the evolving AI landscape - Data-driven and highly organized, with the ability to manage multiple complex searches without sacrificing candidate experience - High ownership, low ego, strong judgment, and a willingness to roll up your sleeves - Leads by example and helps elevate the broader recruiting team - Highly resourceful and fluent with modern AI tools, using them to accelerate research, sourcing, outreach, market mapping, and recruiting operations without sacrificing judgment or the candidate experience COMPENSATION $163,900 - $245,900 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-AD2 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: New York Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW We are looking for a Lead Technical Recruiter to help build Harvey Labs, our AI research organization. You’ll partner closely with our Chief Research Officer and technical leadership to build the team from the ground up, initially focused on post-training talent across data and evaluations, infrastructure, and modeling and training. You’ll own searches end-to-end, develop talent strategies for highly specialized AI talent markets, and help define how we identify and attract exceptional technical talent as Harvey Labs scales. This is a hands-on role with significant ownership. You’ll operate in ambiguity, develop a strong point of view on the AI talent landscape, and serve as a trusted advisor to technical leadership. WHAT YOU'LL DO - Partner closely with our Chief Research Officer and Harvey Labs leadership to translate technical priorities into recruiting strategies - Own full-cycle recruiting across specialized AI/ML, research, and engineering roles - Build deep talent maps across leading AI companies, research labs, startups, academia, and open-source communities - Develop creative, high-touch sourcing and engagement strategies for exceptional talent, from experienced researchers to emerging new grads - Help leaders define new profiles, calibrate talent bars, and evolve search strategies based on market insights - Advise leadership on talent availability, competitive dynamics, compensation, and candidate motivations - Drive searches from initial market mapping through offer strategy, negotiation, and close - Use data and market intelligence to continuously improve our recruiting strategy - Help build scalable recruiting processes and raise the bar for technical recruiting across Harvey WHAT YOU HAVE - 7+ years of full-cycle technical recruiting experience in fast-paced, high-growth environments - Experience recruiting for technical AI research teams or similarly specialized technical roles - Strong aptitude for understanding complex technical domains and evaluating candidate qualifications - Exceptional sourcer who enjoys identifying hard-to-find talent across research labs, startups, academia, open source, and other nontraditional channels - Willing to take creative, white-glove approaches to engaging and closing exceptional talent - Trusted advisor who can build credibility with highly technical leaders and candidates - Comfortable with ambiguity and able to help shape searches when the profile isn't fully defined - Strong instincts for talent and a genuine interest in the evolving AI landscape - Data-driven and highly organized, with the ability to manage multiple complex searches without sacrificing candidate experience - High ownership, low ego, strong judgment, and a willingness to roll up your sleeves - Leads by example and helps elevate the broader recruiting team - Highly resourceful and fluent with modern AI tools, using them to accelerate research, sourcing, outreach, market mapping, and recruiting operations without sacrificing judgment or the candidate experience COMPENSATION $163,900 - $245,900 USD DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74. #LI-AD2 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

Location: Munich; Warsaw; London 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 The Inference Foundation team owns the core of Mistral's inference stack: the inference engine and its orchestration, from the feature set and configuration that serve our models in production to the release machinery that keeps the stack current and production-grade. This is a hybrid position spanning production LLM serving, engine and platform development, and capacity engineering. You will work on three intertwined problems: 1. Optimize the inference stack at scale — feature development and fixes in the engine and orchestrator, squeezing more throughput and lower latency out of every GPU under strict quality-of-service targets. 2. Make capacity elastic — scaling up and down should be cheap and fast, not a performance cliff. 3. Power the training of our frontier models — high-performance serving that keeps RL and post-training loops running at full speed.   What You Will Do INFERENCE ENGINE & ORCHESTRATION - Develop and fix the core of the inference stack — engine and orchestrator — including feature selection, configuration, and tuning for maximum performance at scale - Own the release process for the serving stack: validated, regression-free releases through automated performance gates and progressive rollout - Drive improvements and fixes upstream when the open-source engine is the right place for them PERFORMANCE & CAPACITY AT SCALE - Optimize serving efficiency across the fleet — driving down pod startup time, tackling cold-cache regressions on scale-up, smarter caching and offloading - Optimize and maintain the optimal serving topology — overlap communication and transfers with computation, ensure optimal placement, connectivity, and routing SERVING FOR FRONTIER TRAINING - Build the serving infrastructure that powers RL and post-training for our frontier models - Optimize inference performance across the full spectrum of our workloads   What We're Looking For - Experience building and running ML/LLM services at scale, with clear latency and availability targets - Hands-on experience with inference engines such as vLLM, SGLang, TensorRT-LLM, or others - A solid grasp of inference internals: prefill vs. decode, KV-cache behavior, batching, scheduling, speculative decoding, parallelism strategies - Familiarity with distributed and disaggregated serving architectures - Comfortable debugging across the full stack — CUDA/NCCL, kernels, containers, networking, storage - Python for systems tooling and backend services; PyTorch - Kubernetes for running infrastructure at scale - GPU and networking fundamentals: CUDA runtime, NCCL, InfiniBand/RDMA It Would Be Great If You Have - Demonstrated vLLM/sglang know-how — upstream contributions, or a track record of running in demanding production environments - Hardware-aware optimization for various model architectures - Experience serving MoE models at scale (expert parallelism, expert placement/load balancing) - CUDA/Triton kernel development; Nsight Systems/Compute profiling - Rust and/or C++ in production systems 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: Chicago DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. Senior Quantitative Researcher – Delta One DRW is seeking a Senior Quantitative Researcher (Delta One) to join the FICC options trading business. This individual will serve as an embedded quantitative research lead within an established discretionary and systematic options platform, with a mandate to research, develop, and validate futures-driven systematic strategies that complement and enhance the broader FICC options franchise. This role focuses on delta-one strategy research, quantitative signal generation, systematic futures execution research, and portfolio hedging across global futures markets. The individual will partner closely with options traders and developers to translate research into production strategies and integrate futures-based signals, directional overlays, and risk-efficient hedging frameworks into the broader derivatives platform. This position is suited for someone with deep quantitative expertise, a demonstrated record of research contributing to trading performance, and experience developing scalable systematic models within derivatives markets. Key Responsibilities Research, develop, and validate systematic delta-one futures strategies across global markets, including rates, FX, commodities, and equities. Build and refine quantitative signal generation frameworks to support both standalone futures strategies and options portfolios. Develop and evaluate futures-based hedging methodologies to improve portfolio risk management across the FICC options business. Research directional options overlays grounded in quantitative futures signals, partnering with traders on implementation and evaluation. Model and analyze strategy and portfolio risks, including exposure, volatility, liquidity, and cross-asset correlations. Partner closely with traders, developers, and trading infrastructure teams to productionize research, establish model monitoring, and improve execution. Conduct rigorous research, backtesting, out-of-sample validation, and performance attribution, incorporating realistic transaction costs and execution constraints. Analyze live strategy performance to identify model weaknesses, changing market conditions, and opportunities for improvement. Continuously refine models to improve signal quality, robustness, scalability, and capital efficiency. Develop quantitative frameworks to inform portfolio construction, capital allocation, and risk budgeting within the FICC platform. Qualifications 2+ years of experience in quantitative research supporting systematic trading, preferably in futures and listed derivatives. Proven track record of developing quantitative signals or models that have been deployed in production and contributed to trading performance. Strong understanding of derivatives pricing, volatility dynamics, and risk modeling. Deep experience in signal research, statistical modeling, and alpha generation. Expertise in research design, backtesting, and model validation, including addressing overfitting, data leakage, and implementation costs. Fluency in Python and experience working with large-scale financial datasets. Strong knowledge of market microstructure and execution modeling. Ability to independently lead research projects while collaborating effectively with traders and developers. Preferred Background Experience researching strategies across global futures markets, including equities, rates, commodities, and FX. Experience integrating options strategies within systematic futures frameworks. Familiarity with portfolio construction, capital allocation, and risk budgeting models. Experience working within or alongside an options trading desk. Experience supporting the full research lifecycle, from hypothesis development and empirical testing through production implementation and ongoing evaluation. Advanced degree in Mathematics, Statistics, Physics, Engineering, Computer Science, or a related field The annual base salary range for this position is $150,000 to $250,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts. For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice . California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice . #LI-JW1

Location: San Francisco, CA Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Sierra was co-founded by Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/ who first met while working together at Google over 20 years ago. Bret currently serves as Chairman of the Board of Open AI. Previously, he was co-CEO of Salesforce and CTO of Facebook. Clay spent 18 years at Google, where he most recently led Google Labs. Sierra’s Applied Research team advances the quality, speed, and cost efficiency of the models powering our agents across a wide range of tasks. Our work spans post-training open-weight models for specialized capabilities and pioneering new approaches to voice AI, turning research breakthroughs into reliable production systems. WHAT YOU’LL DO - Tackle unsolved applied AI and ML problems. Pushing the boundaries of post-training, voice AI, and long-horizon task execution, building agents that can reason, adapt, and reliably carry out complex tasks for customers. - Determine when to build specialized models and when to use externally provided frontier intelligence, balancing quality, speed, and cost to deliver customer value. - Turn ambiguous product and customer problems into well-framed machine learning problems. - Develop, fine-tune, evaluate, and deploy models that improve Sierra’s customer-facing AI agents. - Advance our post-training work, from supervised fine-tuning toward reinforcement learning and long-horizon optimization. - Build rigorous evaluations that connect model performance to real-world agent quality. - Work with large-scale, proprietary datasets spanning text and audio interactions. - Collaborate across Sierra while taking ideas from experimentation through production deployment and customer impact. WHAT YOU’LL BRING - Strong experience building and deploying production machine learning and AI systems. We welcome backgrounds across applied ML, including search, ranking, recommendations, advertising, language, and speech. - Excellent judgment in framing product problems as ML tasks and selecting the simplest & most effective approach. - Experience working deeply with data, experimentation, evaluation, and model iteration. - A practical, evidence-driven approach to ML, with strong judgement around when a problem calls for modeling and when a simpler solution will deliver the best outcome. - The ability to operate with high agency and work across the stack when needed to deliver an outcome. - Alignment with Sierra’s values, including Craftsmanship, Customer Obsession, and Competitive Intensity. - A degree in computer science, machine learning, or a related field, or equivalent professional experience. EVEN BETTER… - Experience with supervised fine-tuning or reinforcement learning. - Experience in search, ranking, recommendations, or advertising systems. - Experience training and deploying language, speech, or multimodal models. - Experience designing model evaluations tied to real-world product outcomes. - Experience working with large-scale consumer datasets or high-volume ML products. - Contributions to applied ML research or benchmarks. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits - Lunch, as well as delicious snacks and coffee to keep you energized when working onsite - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region and employment type, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply through the link on this page even if your experience doesn't precisely match the job description. Sierra is a proud equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state or local laws, including veteran status and disability status. Hiring decisions are made by people, based on merit. If you need a reasonable accommodation for a disability, a religious practice, pregnancy or any related condition at any point in the application or interview process, contact us at accommodations@sierra.ai. Requests are handled confidentially and do not affect your candidacy. We will consider qualified applicants with arrest and conviction records in accordance with applicable fair chance laws.

Location: New York DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. DRW is looking for a Quantitative Researcher to join our growing Prediction Markets team. The team develops systematic trading strategies across a wide range of prediction markets. This role combines quantitative modeling, market data analysis, and strategy development to identify opportunities in rapidly evolving markets. You will work closely with traders and engineers across the full strategy lifecycle, from initial research and model development through production deployment and live performance analysis. What you’ll do: Apply statistical and machine learning methods to develop predictive models and trading signals Analyze large and diverse datasets to identify market opportunities and inefficiencies Research how short-term signals from related financial markets can improve prediction-market pricing and trading Conduct research into pricing, market making, market microstructure, execution, and risk management Conduct rigorous quantitative research and evaluate strategies through backtesting and simulation Develop analytical tools to monitor performance and improve live strategies Collaborate with traders and engineers to translate successful research into production trading systems Explore new products, datasets, and approaches as the prediction-markets business expands What we’re looking for: 2+ years of experience in quantitative research, systematic trading, data science, or a related field Degree in a quantitative or technical discipline such as mathematics, statistics, computer science, engineering, physics, or economics Strong knowledge of probability, statistics, and quantitative modeling Experience conducting research with large, noisy, real-world datasets Strong programming skills, particularly in Python Ability to formulate and independently drive open-ended research problems Strong attention to detail and a rigorous approach to testing and validating results Ability to communicate complex ideas clearly and work effectively with traders, researchers, and engineers Intellectual curiosity and a genuine interest in financial markets and prediction markets Additional experience that would be helpful: Systematic or electronic trading High-frequency or short-horizon signal research Probabilistic forecasting or machine learning Strategy backtesting and performance analysis Experience moving quantitative research into live production The strongest candidates will combine quantitative rigor with practical judgment, intellectual curiosity, and a willingness to take ownership of difficult, open-ended problems. The annual base salary range for this position is $200,000 to $300,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts. For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice . California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice . #LI-GV1

Задачи: — Создать систему мониторинга, которая регулярно сверяет инвестиционные тезисы с новыми данными и показывает, подтверждается тезис, слабеет или требует пересмотра. — Создать point-in-time хранилище данных: рыночные и фундаментальные данные, документы SEC, стенограммы звонков, новости, внутренняя аналитика. — Проверять инвестиционные гипотезы на исторических данных (backtesting) и разрабатывать сигналы в дополнение к фундаментальному анализу. — Проводить портфельную аналитику: концентрация, факторные экспозиции, ликвидность, сценарные риски, размер позиций. — Развивать AI-агентов в исследовательском процессе и оценивать качество их работы. Требования: — Сильная база в математике, статистике и машинном обучении. — Опыт от 3 лет в quantitative research или data science на финансовых данных. — Опыт доведения модели или сигнала до практического применения с демонстрацией проверки результата. — Опыт backtesting на point-in-time данных с пониманием look-ahead bias, survivorship bias и переобучения. — Умение самостоятельно строить пайплайны данных и писать надёжный, тестируемый код на Python и SQL. — Опыт построения систем на LLM с измеримым качеством: evaluation, тестовые наборы, контроль ошибок. — Понимание фундаментального анализа и портфельного риска для формализации инвестиционного тезиса. — Уверенный английский язык. Условия: — Формат работы: full-time, удалённо. — Конкурентная оплата труда и годовой бонус по личным результатам и результатам компании. — Собственный бюджет на инфраструктуру и найм команды при подтверждении эффективности системы.

Задачи: — Создать систему мониторинга, которая регулярно сверяет инвестиционные тезисы с новыми данными и показывает, подтверждается тезис, слабеет или требует пересмотра. — Создать point-in-time хранилище данных: рыночные и фундаментальные данные, документы SEC, стенограммы звонков, новости, внутренняя аналитика. — Проводить backtesting и разрабатывать модели для проверки инвестиционных гипотез на исторических данных, создавать сигналы в дополнение к фундаментальному анализу. — Анализировать портфель: концентрация, факторные экспозиции, ликвидность, сценарные риски, размер позиций. — Развивать AI-агентов в исследовательском процессе и оценивать качество их работы. Требования: — Сильная база в математике, статистике и машинном обучении. — Опыт от 3 лет в quantitative research или data science на финансовых данных. — Практический опыт доведения модели или сигнала до применения с демонстрацией проверки результата. — Опыт backtesting на point-in-time данных с пониманием look-ahead bias, survivorship bias и переобучения. — Умение самостоятельно строить пайплайны данных и писать надёжный, тестируемый код на Python и SQL. — Опыт построения систем на LLM с измеримым качеством: evaluation, тестовые наборы, контроль ошибок. — Понимание фундаментального анализа и портфельного риска для формализации инвестиционного тезиса. — Уверенный английский язык. Желательно: — Опыт построения систем на LLM с измеримым качеством: evaluation, тестовые наборы, контроль ошибок. — Опыт работы на buy-side или в прямом взаимодействии с портфельными управляющими. Условия: — Работа с реальным портфелем, инструменты тестируются в инвестиционном процессе. — Доступ к профессиональным источникам данных и современным AI-инструментам. — Конкурентная оплата труда и годовой бонус по личным и корпоративным результатам. — Собственный бюджет на инфраструктуру и найм команды при подтверждении эффективности системы.

Задачи: — Повышать скорость экспериментов команды, ускорять запуск, получение и анализ результатов. — Поддерживать и развивать JAX фреймворк для обучения моделей, обеспечивая масштабируемость и эффективность на TPU. — Улучшать качество данных для обучения моделей, выявлять и исправлять проблемы, повышая точность. — Анализировать точность продакшн-моделей, строить системы оценки и определять приоритетные улучшения. — Переводить исследовательские прототипы в продакшн-системы, рефакторить и модернизировать архитектуры и инфраструктуру. — Оптимизировать продакшн-инференс для речевых моделей, включая архитектуру сервиса и техники квантования, спекулятивного декодирования. — Исследовать и устранять узкие места в производительности на всех уровнях стека, от низкоуровневых ядер (XLA, Pallas) до системного дизайна. — Сотрудничать с исследователями, инфраструктурной и продакшн-командами для выявления и устранения проблем. Требования: — Экспертное владение JAX и TPU, включая экосистему Flax, Optax, XLA. — Дисциплина измерений: определять успех заранее, критически оценивать результаты. — Готовность работать с полным пайплайном, включая данные и оценку. — Опыт оптимизации систем инференса для продакшна, желательно с LLM или речевыми моделями. — Глубокое понимание распределённого обучения, современных систем глубокого обучения и ML-инфраструктуры. — Знание современных техник оптимизации инференса: непрерывная пакетизация, управление KV-кэшем, стратегии шардирования, квантование. — Энтузиазм к рефакторингу и улучшению существующих систем. — Сильные навыки Python; опыт C++ или Rust для низкоуровневой работы — плюс. — Отличные коммуникативные навыки и умение работать в команде. Бонус: — Знания в области Speech-to-Text: архитектуры ASR, аудиопроцессинг, стриминговый инференс. Условия: — Удалённая работа. — Полная занятость. — Зарплата в США от $270,000 до $310,000 в год. Компания AssemblyAI — лидер в области Voice AI, обрабатывает миллионы часов аудио и API вызовов ежедневно, работает в режиме meritocracy без бюрократии, с высокой степенью ответственности и влияния каждого сотрудника.

Задачи: — Проводить проактивный поиск угроз и анализ цепочек атак (kill chain) в системах Stripe и внешних данных. — Применять и развивать многоуровневую таксономию FT3 для стандартизации разведданных об угрозах. — Сотрудничать с командами Fraud Intelligence, Fraud Ops, Strategy, Risk, Onboarding и Security для интеграции и автоматизации потоков разведданных. — Переводить результаты исследований в практические рекомендации по контролю угроз, включая политику, технические системы, рабочие процессы поддержки и механизмы обнаружения. — Использовать агентные автоматизированные тестовые фреймворки для моделирования поведения злоумышленников, проверки эффективности контролей и создания регрессионных сценариев. Требования: — Опыт не менее 5 лет в области разведки угроз, поиска угроз или технического реагирования на инциденты в кибербезопасности, борьбе с мошенничеством или доверительных доменах. — Опыт анализа больших и сложных наборов данных с использованием аналитических инструментов для выявления аномалий, анализа поведенческих трендов и решения сложных задач мошенничества. — Высшее образование (бакалавр или магистр) в области компьютерных наук, кибербезопасности или смежной технической области, либо эквивалентный практический опыт. — Экспертное владение Python и SQL, опыт автоматизации рабочих процессов, создания инструментов для расследований и запросов к большим данным. — Практический опыт анализа логов (приложений, API, сетевых событий), цифровой криминалистики и методологий киберрасследований. — Сильные коммуникативные навыки для перевода сложных технических исследований в понятные и применимые рекомендации для межфункциональных команд. Предпочтительные квалификации: — Глубокое понимание мотиваций, инфраструктуры и тактик злоумышленников, специфичных для финансового мошенничества (например, ATO, Card Testing, Credential Stuffing). — Знакомство с таксономиями FT3 или MITRE ATT&CK. — Владение платформами для обработки и анализа данных, такими как Databricks, Trino, PySpark, Pandas, Scikit-Learn. — Опыт работы с платформами разведки угроз (TIPs), тактическими потоками угроз, OSINT и разведданными о взломах. — Навыки создания или использования агентных LLM-инструментов, систем автоматизированного тестирования и фреймворков валидации контролей для моделирования поведения злоумышленников в масштабе. — Участие в отраслевых конференциях, вебинарах, группах обмена угрозами и наличие профессиональных сертификатов (например, GCTI, GCFA, OSCP).

Задачи: — Полный цикл исследований по краткосрочной микроструктуре, LP/хеджированию, исполнению, межплощадочным сигналам, распределению риска и смежным задачам crypto/DeFi — Дизайн исследования: гипотеза, target/разметка, baseline, метрики, причинно корректная OOS-проверка, анализ режимов и явные критерии GO/NO-GO — Работа с данными: поиск источников, выравнивание времени, контроль качества, построение признаков и воспроизводимые контракты данных — ML/DL по структуре задачи — RL или другие методы последовательного управления - только когда они действительно оправданы — Реалистичная симуляция и торговая экономика: комиссии, проскальзывание, ликвидность, задержки, adverse selection, impact, fill assumptions, хеджирование и синхронизация DEX/CEX — Paper/shadow-стратегии, анализ sim-to-real и совместная работа с quant developer при переносе доказанных решений в production — Инженерный стандарт исследования: воспроизводимые эксперименты, чистый Python, критичные проверки, мониторинг и дисциплинированное использование LLM/агентов Требования: — Проверяемый опыт 2-3 Quant/ML проектов, где кандидат лично отвечал за существенную часть цепочки от постановки задачи и данных до проверки, кода и решения о внедрении либо GO/NO-GO — Отличный Python и сильная инженерная база: кандидат сам пишет, отлаживает и ревьюит исследовательский код — Сильная статистика, вероятность, оптимизация и работа с временными рядами: временную зависимость, leakage, selection bias, uncertainty и честную OOS-проверку — Глубокое практическое понимание микроструктуры и исполнения: order book/flow, liquidity, latency, fees, slippage, adverse selection, impact, sizing и hedging — Сильное практическое владение ML/DL для последовательных финансовых данных и способность отличать реальный сигнал от оптимизации метрики — Высокая самостоятельность: структурировать неясную проблему, выбирать наиболее информативный эксперимент, быстро останавливать слабые гипотезы и принимать решения на основании доказательств — Рабочее понимание структуры crypto-рынка — Прямой опыт DeFi/DEX будет плюсом, но сильный CEX/microstructure опыт может его компенсировать при быстрой адаптации

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

Location: United States Bring your monitoring expertise to the forefront of innovation. We are looking for a Clinical Research Associate (CRA) to join our A-team (remote; with travel). 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. At Allucent™, we are dedicated to helping small-medium biopharmaceutical companies efficiently navigate the complex world of clinical trials to bring life-changing therapies to patients in need across the globe. At Allucent we are big enough to deliver and small enough to care. We know all our colleagues by name and work together as a team to make everyone SHINE. The role 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. You will be a mentor for junior team members and contribute to grow our success. You will travel throughout the United States. Therapeutic Areas: Oncology, Cell & Gene Therapy, and/or Neuroscience Preferred location: West Coast, USA 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. Mentor and support junior CRAs , sharing knowledge and best practices. Requirements Who are we looking for: You’re an experienced CRA / monitor 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. Preferred Location: West Coast, United States Therapeutic Areas:Oncology, Cell & Gene Therapy, and/or Neuroscience Experience leading monitoring activities in complex trials with a minimum of at least 3-5 years’ experience. Experience in complex therapeutic areas such as cell and gene therapy, radiopharmaceutical preferred. Strong understanding of ICH-GCP and regulatory guidelines. Clear and confident communicator in English. Comfortable working independently and managing priorities. Willingness to travel throughout the United States, as required. Effective clinical monitoring skills (all kind of visits mastered) 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) Opportunity for remote/hybrid* working depending on location Leadership and mentoring opportunities Participation in our enriching Buddy Program as a new or existing employee Internal growth opportunities and career progression Financially rewarding internal employee referral program Access to online soft-skills and technical training via internal platforms 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 policy encourages a dynamic work environment, prescribing a minimum of 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-TCW #LI-remote

Location: Yerevan, Armenia Description The Market Research Case & Strategy Analyst evaluates iGaming markets, competitors, and target operators to support Digitain's market entry decisions, commercial strategy, and sales engagement, delivering actionable insights for Sales, Product, and Leadership teams. As Market Research Case & Strategy Analyst, you will assess priority markets, analyze competitor strategies and industry success stories, and identify operators that are strong migration opportunities for Digitain. Your work will directly shape which markets we enter, when and how, and which operators we pursue. Responsibilities Evaluate target markets for product launches, sales activation, and strategic entry, analyze competitors’ entry experiences, launches, regulatory adaptations, and operational challenges to identify practical lessons Analyze market growth, trends, and maturity across macroeconomic, demographic, fiscal, regulatory, competitive, and operational indicators; assess industry success stories for applicable drivers of revenue growth, player acquisition, and innovation adoption Monitor industry investment and expansion trends; evaluate business strategies, growth models, and partnerships across the iGaming market Track existing and upcoming regulations, B2B licensing frameworks—including those in planning—and licensing tenders to identify entry requirements, timely sales opportunities, and operators needing platform solutions Assess market attractiveness through size, growth, competition, regulatory stability, and business impact; benchmark key competitors’ entry strategies, operations, pricing, and long-term positioning Develop forward-looking market assessments to identify early-entry advantages ahead of leading competitors Evaluate market-specific product readiness across platform capabilities, sportsbook, casino content, payments, and compliance tools; research operators’ integrations, supported languages, content providers, and technical partners to identify gaps and adaptations Collaborate with Market Intelligence, Product Innovation, and Product teams to integrate insights into actionable analyses and document required adaptations or new tool recommendations in execution-ready formats Work with Legal and Compliance teams to assess regulatory gaps and market-specific technical compliance obligations Produce market entry reports, opportunity briefs, gap analyses, case studies, and strategic briefs for Sales, Product, and Leadership; recommend entry timing, product priorities, and investment focus, contributing to BRDs, PRDs, budgets, and financial documentation Continuously monitor researched markets for regulatory and competitive changes, updating assessments and recommendations Source and validate research using industry intelligence, regulatory publications, financial reports, competitor filings, databases, interviews, and historical performance metrics Identify potential platform migration targets and conduct pre-engagement research using operator news, public announcements, and industry publications Analyze target operators’ financial and performance indicators, including GGR, traffic, and player base Assess operators’ geographic footprint and technology stack, distinguishing between in-house and third-party platforms Requirements Bachelor's or Master's degree in Economics, Business, Finance, International Relations, or a related field 3+ years of experience in market research, market entry strategy, strategy consulting, competitive or sales intelligence, or business analysis, ideally within iGaming. Experience in fintech, telecom, or other heavily regulated multi-market industries will also be considered Demonstrated experience conducting market entry assessments and in-depth case studies of companies, ideally with direct influence on go/no-go or timing decisions Strong analytical and strategic thinking skills, with the ability to synthesize complex multi-source data into clear, executive-ready reports and presentations Experience working with company financials and performance metrics (GGR, traffic, revenue). Familiarity with iGaming operator economics and platform/technology stacks is a strong advantage Exposure to product readiness or gap analysis work across platform, sportsbook, casino, or payment capabilities is a strong plus Understanding of compliance, licensing, and regulatory tender processes, or the ability to work closely with Compliance and Legal teams Excellent research and written communication skills, with a proven ability to produce decision-ready reports, case studies, and strategic briefs Proficiency in Excel/data analysis tools. Experience with BI, market intelligence, or CRM platforms is a plus Fluent English (written and spoken). Knowledge of additional languages is a plus

Location: Yerevan, Armenia Description The Product Innovation & Research Analyst is responsible for deep-diving into the iGaming product ecosystem — evaluating competitor features, identifying innovation opportunities, and translating market insights into structured product intelligence that drives Digitain's roadmap and competitive positioning. This role sits at the crossroads of product thinking and competitive intelligence. You will work closely with Digitain's cross-functional product teams — Platform, Sportsbook, Live Casino, Relum, and Paydrom — to evaluate what competitors are building, what operators need, and where the greatest opportunities for differentiation lie. Responsibilities Conduct deep-dive product research across the iGaming ecosystem: platforms, aggregators, sportsbooks, live casino providers, virtual sports, and payment solutions Analyze product innovations, features, and technologies identified through both independent research and insights from the Market Intelligence Expert Identify product features and capabilities with proven or potential business impact: revenue uplift, player engagement, retention, or market differentiation Initiate proposals for new product sets or market-specific solutions when research identifies them as critical to competitive success or regional growth Evaluate potential impact, scalability, and strategic value of identified features — including quantitative assessments of revenue growth, user engagement, technical complexity, and time-to-market Conduct market- and region-specific product gap analyses, including local player preferences, regulatory requirements, and localization complexity assessments Assess Digitain's platform readiness for localization in specific countries; prepare initial resource estimations to support full market entry Identify and document operator pain points via social media, conference content, podcasts, and industry news; translate findings into structured insights for the Sales team Collaborate with cross-functional product teams to validate research, gather expert input, and present detailed analyses Track adoption and performance of competitor product features post-launch to validate impact assumptions and refine future recommendations Prepare comprehensive documentation of research outcomes to support BRD, PRD, and strategic planning processes Stay current on emerging product and technology trends (AI personalization, gamification, new betting formats, alternative payments) and proactively surface high-potential opportunities Requirements Bachelor's degree in Business, Economics, Marketing, Computer Science, or a related field 3+ years of experience in product research, product management, business analysis, or competitive intelligence — ideally within iGaming (platforms, sportsbook, live casino, payments); experience in fintech, SaaS, or gaming related industries also considered Demonstrated experience conducting deep-dive product research and translating findings into structured, actionable recommendations Strong analytical skills, with the ability to assess product features for scalability, technical complexity, and time-to-market Experience evaluating product features for business impact (revenue, engagement, retention) and presenting findings to cross-functional stakeholders Familiarity with the iGaming product landscape: platforms, aggregators, sportsbook providers, live casino, virtual sports, and payment solutions Excellent research skills, with the ability to source and analyze insights from conferences, podcasts, social media, industry news, and direct product testing Ability to prepare clear documentation to support BRD/PRD and strategic planning processes Ability to work closely with cross-functional product teams to validate research and gather expert input Ability to proactively propose and advocate for new product ideas and market-specific solutions based on research findings Fluent English (written and spoken); additional languages are a plus

Location: West Palm Beach, Florida, United States Graham Capital Management, L.P. (collectively with its affiliates, "Graham") is an alternative investment manager founded in 1994 by Kenneth G. Tropin. Specializing in discretionary and quantitative macro strategies, Graham is dedicated to delivering strong, uncorrelated returns across a wide range of market environments. As one of the industry’s longest-standing global macro and trend-following managers, Graham remains committed to innovation, evolving its strategies through a robust investment, technology, and operational infrastructure. Graham harnesses the synergies between its discretionary and quantitative trading businesses to offer a broad suite of complementary alpha strategies, each built on the principles of thoughtful portfolio construction, active risk management, and diversification by design. Graham invests significant proprietary capital alongside its clients – including global institutions, endowments, foundations, family offices, sovereign wealth funds, investment management advisors, and qualified individual investors – reinforcing alignment of interests across all strategies. The foundation of Graham’s sustainability and success is the experience and contributions of its people. The firm seeks to cultivate talent, encourage the diversity of ideas, and respect the contributions of all. In turn, each employee shares in the responsibility of strengthening those around them. Description Graham is seeking a Quantitative Research Developer to join our Quantitative Strategies team. The individual will research and develop ways to improve Graham’s current trading code base and create new systematic trading signals to complement and diversify the firm’s main strategies. The individual will maximize performance and competitiveness by utilizing advanced methods in quantitative analysis and software development. Responsibilities Create production code for new trading signals Ensure the efficiency and accuracy of existing production code Research and develop methods to make existing trading signals more efficient, profitable and robust Research and develop new signals that trade futures and FX markets that complement and diversify production strategies in terms of style, source of alpha and markets traded Follow robust research and development procedures to reduce differences between simulated and actual performance Work collaboratively in a research team environment, using common development tools to facilitate robust implementation of research as well as production versions of trading systems Interact with other departments – technology, operations, trading, marketing, and accounting - to ensure current and proposed ideas are implemented, monitored and executed efficiently and accurately Regularly present findings and ideas to management and investment committee Complete other projects as requested by senior management Requirements PhD or MS in a quantitative field 2+ years related experience in systematic futures and/or FX trading on the buy side Exposure to securities and derivatives markets and investment processes with knowledge in mid-to-low frequency systematic strategies Advanced programming experience in languages suited for quantitative research and strategy implementation – python and/or MATLAB preferred Ability to synthesize complex topics into easily digestible written commentary Strong communication skills – both written and verbal This role requires commuting into our West Palm Beach, FL office Mondays through Fridays. Please note that our central Quantitative Research team sits out of Rowayton, CT but the manager for this new hire will be based out of West Palm Beach, FL. Base Salary Range The anticipated base salary range for this position is $200,000 to $275,000. The anticipated range is based on information as of the time this post was generated and does not include any discretionary bonus or benefits (see eligibility below). The applicable annual salary or hourly rate paid to a successful applicant will be determined based on multiple factors, including without limitation the nature and extent of prior experience, skills, and qualifications.  This wage range may be modified in the future. In addition, the employee who fills this role will be eligible for a discretionary annual bonus, as well as a wide array of benefit programs, such as medical and life insurance, 401(K) plans, and access to other healthcare programs. Notes: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, benefits, or any other form of compensation that a particular employee may be eligible for remains in the Company's sole discretion unless and until paid and may be modified at Graham’s sole discretion, consistent with the law. Other Graham is committed to providing equal employment opportunity to all employees and applicants for employment without regard to their race, color, religious creed, gender, age, national origin, ancestry, alienage, citizenship status, handicap, disability, marital status, sexual orientation, gender identity, pregnancy, childbirth or other related conditions, military status, genetic information, or any other personal characteristics protected by applicable law. This policy applies to all terms and conditions of employment, including hiring, placement, promotion, layoff, termination, transfer, leave of absence and compensation. Graham offers health benefits to eligible full-time U.S. employees, including medical, dental, vision, life and disability insurance, as well as other voluntary benefits such as spending accounts (HSA and FSA), and a profit contribution retirement plan.  All employees also receive paid vacation and sick leave.  Benefits eligibility is dependent upon a variety of factors, including employee classification and applicable waiting periods.  Benefits are subject to change and may differ for non-U.S. roles.

Предлагается стипендия Post-lauream research scholarships для иностранных студентов, планирующих обучение в Университете Палермо. Стипендия полностью покрывает расходы на обучение. Крайний срок подачи заявок — как можно скорее.

Задачи: — Решать сложную исследовательскую задачу на стыке probabilistic ML, sequential decision making и моделирования поведения агентов. — Моделировать поведение участников в стохастической многоагентной среде с частичной наблюдаемостью и использовать эти прогнозы для принятия решений в условиях неопределённости и ограниченного inference budget. — Проводить эксперименты и доказывать, почему новый подход лучше сильного baseline. Требования: — Опыт самостоятельной разработки или существенного улучшения ML/математических методов. — Умение работать с неопределённостью. — Опыт в одном или нескольких направлениях: RL / sequential decision making / POMDP / world models; probabilistic & Bayesian ML, latent-variable models, uncertainty estimation; behavior / opponent modeling, multi-agent systems; off-policy evaluation, importance sampling, doubly robust estimation, variance reduction; Monte Carlo / Markov models / stochastic optimization; algorithmic trading / HFT / pricing / decision systems с реальными ограничениями на latency. — Сильная математическая база, опыт собственных R&D-разработок и публикации либо сильный applied research опыт. — PhD будет плюсом, но не обязателен. — Важна способность подробно разбирать свой проект: проблема → baseline → ваша идея → альтернативы → эксперимент → измеримый результат. Условия: — Формат работы: remote. — Контракт от 3 месяцев. — Приоритетно full-time, но возможен part-time для сильных кандидатов. — Данные и вычислительная инфраструктура предоставлены, высокая исследовательская свобода. Стек для прототипирования: Python, PyTorch.