Вакансии

— Design and run product experiments end to end - form hypotheses, define test duration and required sample size, assess whether the expected result is achievable, evaluate A/B tests and determine statistical significance;

Роль объединяет анализ больших данных, ETL и описание взаимодействия систем. — Python, SQL, реляционные базы, статистика и вероятность.

Вести сложные продуктовые проекты и инициативы, направленные на улучшение пользовательского опыта и рост ключевых бизнес-показателей. Формировать подход к продуктовой аналитике: определять необходимые бизнесу метрики, валидировать данные и использовать инсайты для принятия взвешенных продуктовых решений.

• Configure and troubleshoot GTM, GA4, and Consent Mode v2. • Implement dataLayer schemas and prepare technical specs for developers.

Go: опыт от 3 лет, глубокое знание языка, конкурентности, runtime, GC, модели памяти и Generics. Профилирование (pprof, trace), оптимизация и разработка высоконагруженных, распределённых и отказоустойчивых систем.

Location: Paris; 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. As a Research Engineer on the Orchestral team, you will help build the agentic platform we use to train and evaluate our models. Orchestral is the system our researchers rely on to run training and evaluation at scale — from the rollout engine that powers agentic workflows to the infrastructure that keeps their workloads running reliably. What you build becomes the foundation the whole science team works on. Your work will span the platform's core: the library, tooling, abstractions and rollout engine — including new capabilities like long-running tasks, subagents and RL features — and the machinery that runs data and jobs at scale, with a focus on resiliency, routing and request handling. You will own significant pieces end to end, from design to production. This is a software engineering role rather than an ML or infrastructure-operations one: RL or PyTorch experience is not required, and you will spend your time building the platform, not operating it. You will be building a distributed RL system, with the scientists as your users. WHAT YOU WILL DO - Design and build the core of the Orchestral platform: the library, abstractions and tooling researchers use to train and evaluate models. - Build and evolve the rollout engine, shipping new capabilities such as long-running tasks and subagents. - Run Orchestral as a production system: keep training and evaluation workloads reliable at scale. - Improve how data and jobs flow through the platform as usage grows — scheduling, routing and request handling. - Treat researchers as your users: understand their workflows and turn recurring needs into robust, shared tooling. - Raise the bar on engineering quality across the platform: testing, code review, CI/CD, observability and documentation. - Contribute to open-source rollout-engine and agent-infrastructure projects where it benefits the platform. WHAT WE'RE LOOKING FOR - Experience directly building and debugging complex distributed systems at scale, with an emphasis on reliability and scalability. - Strong Python skills and solid software-design instincts: testing, code review, CI/CD. - A builder mindset: you have constructed systems from the ground up, not just operated polished ones. - A track record in small teams running complex systems at scale — for example in finance, crypto or ad tech. - Self-starter, low-ego and collaborative, with a product mindset toward your users. - Curiosity about ML and RL — this experience is not required, but a desire to learn is. NICE-TO-HAVES - Hands-on experience with Ray or similar distributed-computing frameworks. - Open-source contributions, especially to rollout-engine or agent-infrastructure projects such as SLIME, verl or PrimeRL. - Experience building or working with agentic workflows and environments. 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.

• 5+ лет опыта в аналитике, преимущественно в продуктовой. • Сильный SQL, хорошая техническая база, Python.

Location: Санкт-Петербург Управление развития малого бизнеса в поиске бизнес-аналитика. Обязанности ### **Тебе предстоит:** \- искать и анализировать данные из разных источников, разрабатывать математические модели \- работать в Excel, как продвинутому пользователю: базовые, логические и текстовые функции, ВПР/ИНДЕКС+ПОИСКПОЗ, сводные таблицы \- визуализировать и интерпретировать результаты анализа (презентации в PowerPoint) \- подготавливать регулярные отчеты по работе партнёрского канала \- ежедневно взаимодействовать со смежными подразделениями по вопросам учета сделок и учета активностей территориальных менеджеров ММБ \- проверять гипотезы на основе данных, участвовать в развитии системы отчетности \- проводить аналитические исследования \- собирать и анализировать требования к продукту, подготавливать техописания для разработки и усовершенствования модели работы партнерского канала \- разрабатывать архитектурные и аналитические артефакты на основе бизнес-требований \- участвовать в обсуждении и усовершенствовании продукта и модели работы малого бизнеса. Требования ### **Мы ждём от тебя:** \- высшее техническое или экономическое образование \- опыт анализа больших объемов данных, построения моделей и прогнозирования \- знание математической статистики и методов статистического анализа \- опыт автоматизации/оптимизации процессов \- владение Python понимание базовых алгоритмов и математики \- опыт подготовки ТЗ для разработчиков, работы с Confluence \- знание форматов обмена данными: XML \- навыки работы с генеративным AI: опыт создания и использования AI‑агентов, использование GigaChat, Kandinsky и аналогов, инструментальное владение AI для анализа, генерации и автоматизации. Условия ### **Что мы предлагаем:** * уникальную систему онлайн обучения Сбера для карьерного развития и роста * расширенный ДМС и льготное страхование для семьи * бесплатную подписку СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * офис пл. Карла Фаберже, 8.

Чем предстоит заниматься Развивать Incident & Problem Management внедрять и развивать единый процесс управления инцидентами; формировать культуру postmortem-разборов без поиска виноватых;

Анализировать требования и разработывать тест-кейсов; Писать функциональные тесты на Playwright (Python);

Thinking Machines Lab is looking for a Software Engineer Production Inference Distributed Inference to build and operate distributed production systems for large-scale model serving.

Задачи: — Автоматизация торговых операций — Разработка моделей управления рисками на основе искусственного интеллекта — Анализ эффективности торговых операций Требования: — Опыт работы с машинным обучением — Знание SQL — Опыт работы с большими языковыми моделями (LLM) — Опыт работы с LangChain — Знание MLOps — Опыт обнаружения аномалий — Опыт финансового контроля — Владение Python — Опыт работы с OpenAI API Условия: — Гибридный формат работы в Лондоне

Nscale is looking for an Infrastructure Operations Engineer to deliver data centre projects, monitor critical systems, resolve incidents, automate operations, and support customer infrastructure needs.

Location: London Workplace: OnSite Company Description We’re http://checkout.comCheckout.com http://Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started. ABOUT THE ROLE As an Associate in Strategic Finance, you'll focus on turning financial and commercial data into clear insight - enabling leadership to deeply understand our business and the drivers of performance. You’ll partner with Data Engineering, Finance and cross-functional stakeholders, and build analytical workflows to support fast and data-driven decision-making. WHAT YOU’LL BE DOING - Analyse commercial and business performance - evaluating the full P&L and measuring ROI in order to help the business assess where it is creating value. - Translate ambiguous requests from leadership, Finance and cross-functional stakeholders into clear, decision-ready insights. - Craft executive-style deliverables, which may include decks, models, written documents or AI-powered apps. - Leverage AI tooling as a force multiplier to build and automate reusable analytical workflows that enable your stakeholders to quickly understand performance. - Drive continuous reporting improvements, standardisation, and simplification whilst documenting definitions and limitations - leaving no room for approximation. - Collaborate directly with Data Engineering and Data Science to support the development and enhancement of our core financial data models, and the context layer that enables AI agents to leverage that data. - You will be empowered to work directly with Finance and Data partners to scope requirements and deliver initiatives end-to-end. WHAT WE LOOK FOR ESSENTIAL CRITERIA - You’ll have 3+ years of relevant experience in data-driven and analytical roles, and hold a bachelor’s or master’s degree in a quantitative or business discipline. - Strong analytical thinking: you’re comfortable working with numbers, identifying the underlying patterns and drawing sound conclusions. - Excellent verbal and written communication skills: you have the ability to adjust your style to suit different perspectives and seniority levels. - Commercial curiosity: you want to dive into the details to understand how merchant, product, and commercial dynamics affect financial performance. - Confidence with data tools: You have strong spreadsheet skills and experience with BI tooling and data platforms, or demonstrate a clear aptitude and willingness to learn. Python and SQL experience is a plus. - Exceptional attention to detail: you rigorously validate data, pressure-test assumptions, and transparently communicate analytical limitations. - You’ve used AI hands-on in a business environment to create new tooling or workflows. Additional Information Bring all of you to work We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands. We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here. It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. Life at Checkout.com http://Checkout.com We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. Curious about what it’s like to be part of our team? Visit our Careers Page https://www.checkout.com/careers to learn more about our culture, open roles, and what drives us. For a closer look at daily life at Checkout.com http://Checkout.com, follow us on LinkedIn https://www.linkedin.com/company/checkout/life/ and Instagram https://www.instagram.com/checkout_com/

Operate and maintain BeyondTrust's on-premises and cloud network infrastructure, including routing/switching changes, datacenter resource changes, and routine firewall/security group changes end-to-end across on-prem and cloud environments; Demonstrated proficiency in Administrator/Engineer-level on-premises networking fundamentals.

- Сильный опыт в ML, Deep Learning, NLP и LLM. - Практический опыт создания AI-продуктов, работающих в production и в большом масштабе.

• 8+ лет опыта в прикладном ML/AI с ответственностью за системы end-to-end. • Уверенное владение Python.

• От 3 лет коммерческого опыта в ручном тестировании. • От 2 лет опыта в автоматизации тестирования.