Вакансии

Вакансия предполагает работу на позиции Senior Data Science специалиста с полной занятостью и удалённым форматом в России. Основные задачи включают разработку сервисов для ИИ платформы, предназначенной для создания функциональных агентов и ИИ ассистентов, а также подготовку серверной части для таких агентов, включая тестирование фреймворков и работу с opensource агентами. В обязанности также входит создание сервиса управления реестром и навыками агентов, а также разработка единого сервиса для баз знаний с интеграцией крупных корпоративных источников. Кандидат должен хорошо разбираться в архитектуре и ограничениях современных языковых моделей, иметь опыт работы с embeddings, vector search, RAG, structured output и tool calling. Важны знания принципов проектирования AI-агентов, включая управление состоянием и контекстом, выбор инструментов, контроль автономности и human-in-the-loop. Требуется опыт построения evals для LLM-систем, оценки качества ответов, контроля галлюцинаций и мониторинга поведения, а также понимание рисков, связанных с prompt injection, некорректным tool calling, утечкой данных и избыточными правами доступа. Необходим опыт работы с API языковых моделей, Hugging Face и одним из orchestration-фреймворков, умение оценивать стоимость, задержки и масштабируемость LLM-решений. Желателен опыт в e-commerce, retail или других высоконагруженных продуктовых системах, а также владение инструментами Airflow, MLflow, Kafka, Redis, Kubernetes, Prometheus и Grafana. Кандидат должен иметь опыт эксплуатации GPU-инфраструктуры и оптимизации inference, а также fine-tuning или адаптации LLM, включая LoRA/PEFT. Опыт проектирования agentic workflows или multi-agent систем и понимание принципов информационной безопасности, конфиденциальности и работы с персональными данными также обязательны.

174 000 – 215 000 ₽

Компания "Урал Логистика" приглашает AI-инженера для участия в создании собственной системы обработки документов и данных для грузовых железнодорожных перевозок и связанных услуг. Задачи: — Проектировать и разрабатывать конвейер обработки документов: загрузку, нормализацию, сегментацию, определение структуры и подготовку контекста — Извлекать структурированные данные из договоров, приложений, дополнительных соглашений, актов и других связанных документов — Работать с длинным контекстом, таблицами, пересекающимися формулировками и изменениями условий во времени — Обеспечивать атрибуцию результата к документу, странице и исходному фрагменту — Строить гибридный поиск: полнотекстовый и векторный retrieval, фильтрацию, реранкинг и сбор контекста — Развивать графовое представление документов, сущностей и связей для поисковых и аналитических сценариев — Проектировать агентные и workflow-сценарии: управление состоянием, инструментальные вызовы, повторы, fallback-механизмы и обработку отказов — Создавать эталонные наборы, метрики по полям и регрессионные тесты для оценки извлечения, поиска и генерации — чтобы при смене модели, промпта или retrieval-стратегии было видно, что улучшилось, а что деградировало — Разрабатывать Python-сервисы, API, фоновые задачи и интеграции с внутренними источниками — Участвовать в выборе моделей, постановке экспериментов, fine-tuning и оптимизации локального inference Требования: — Уверенная промышленная разработка на Python уровня middle+ и выше — Опыт с FastAPI или аналогичным фреймворком, асинхронным исполнением, очередями и фоновой обработкой — PostgreSQL и SQL на рабочем уровне — Практический опыт вывода LLM-решений в production — Понимание RAG, structured output, tool calling и многошаговых модельных сценариев — Умение измерять качество: строить эталонные наборы, выбирать метрики, классифицировать ошибки и проводить регрессионное тестирование — Опыт с Docker, Kubernetes и CI/CD — Готовность доводить вертикальную задачу от спецификации и эксперимента до эксплуатации Условия: — Полная занятость и возможность трудоустройства через российское юридическое лицо в штат или через согласованную аутстафф-модель — Основной формат — офис или гибрид — Для самостоятельных специалистов возможна распределённая работа из России Итоговый грейд и масштаб ответственности определяются по результатам собеседования.

Зарплата не указана

Location: New York, NY (HQ) Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE The Applied Science team builds models and tools that solve Ramp’s most critical problems: from underwriting businesses to combatting fraud to making spend management smarter. We’re deeply embedded in the business and provide a quantitative foundation for decision making. As an Applied Science intern, you’ll be a fully integrated member of the team and own your project from start to finish. Working with engineers, product managers, and business stakeholders, you’ll translate complex business needs into scalable machine-learning-driven solutions. This is a chance to apply ML concretely, ship code, and create genuine value for Ramp and our customers. You will focus on exciting problems in areas like: credit, fraud, growth, or our core product.   WHAT YOU’LL DO - End-to-End ML: own the model lifecycle from data exploration and feature engineering to training, benchmarking, deployment, and monitoring - State-of-the-Art AI: leverage the latest Large Language Models (LLMs) to solve novel problems and create new product capabilities for our customers - Versatile Techniques: apply the right tools to the right problems, whether it’s deep learning, gradient boosting, or causal inference - Rigorous Experimentation: quantify the impact of your work through A/B tests and other statistical methods - Collaborate: partner closely with product and business leaders to translate models and insights into actionable strategy and user-facing features   WHAT YOU NEED - B.S., M.S. or Ph.D. Student: currently pursuing a degree in Data Science, Computer Science, Math, Physics, Economics, Statistics, or other quantitative fields with an expected graduation date between Dec 2027 - 2029. Graduate degrees are preferred, but not a must. - Strong ML Fundamentals: solid understanding of the mathematical foundations of machine learning, statistics, probability, and optimization - Strong Interest or Experience with AI: curiosity and drive to integrate cutting edge LLMs and agents into applied solutions - Python Proficiency: good grasp of common Data Science libraries (pandas, scikit-learn, NumPy, PyTorch, etc.) - SQL Knowledge: experience wrangling data in a modern data warehouse (e.g. Snowflake, BigQuery, Redshift, Clickhouse) - Practical Experience: track record of curating datasets and building/evaluating ML models - Strong Communication: ability to clearly explain complex concepts to both technical and non-technical audiences and use data to build a compelling narrative - Bias For Action: a comfort with ambiguity and desire to ship solutions quickly then iterate   NICE TO HAVES - Publications, Projects, or Previous Experience: relevant experience applying AI/ML and demonstrating your passion for the field - Production ML Mindset: knowledge of software engineering best practices applied to ML including version control (Git), testing, and writing maintainable code - Data Orchestration: experience with leveraging modern data orchestration platforms (Airflow, Dagster, Prefect, Metaflow)   COMPENSATION - The monthly rate for this internship is $12,500 USD + housing stipend   RAMP BENEFITS - Apple MacBook - Catered lunches in NYC office Monday-Friday - Weekly coffee stipend BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Location: London Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re building a founding team of Strategic Account Executives in London. Strategic accounts at Baseten are the largest and fastest-growing AI companies in the world. These are the teams defining the future of what AI products and services look like. These accounts can scale rapidly from one token to billions of tokens in a matter of weeks. This role owns these relationships, working directly with founders and engineering leaders on mission-critical and large-scale-AI problems in production—and shaping what we build next. This is a highly technical sale. You’ll trade opinions on the latest open-source model releases, run fast and nuanced evaluations alongside customer engineering teams, and often pulling in SMEs from applied research to infrastructure engineers to win. You’ll bring tight sales fundamentals and process discipline, while maintaining flexibility and creativity in how you run each cycle. This role is pioneering what sales looks like at the bleeding-edge of technology sales. This is a front row seat to the most consequential decisions made at the forefront of Artificial Intelligence. There is no faster place to learn and make an immediate impact.   RESPONSIBILITIES - Own a focused portfolio of high-growth, strategic AI-native accounts end to end — from technical evaluation and initial workload landing through expansion as inference usage scales. - Lead technical evaluations and complex, multi-stakeholder sales cycles from first conversation through close. Bring strong sales fundamentals and process discipline, while staying flexible and creative in how you run each sales cycle. - Build trusted relationships with founders and technical leaders, becoming a credible partner on model, infrastructure, and inference decisions. - Orchestrate stakeholders across applied research, engineering, and leadership to win technical evaluations and solve customer problems. - Bring customer signal back to product, shaping roadmap priorities through the needs and patterns you see in the field. - Stay close after close: help customers expand from an initial workload into additional use cases across the organization.   REQUIREMENTS - 5+ years of sales experience in infrastructure, developer tools, data, or another consumption business, with a record of closing complex technical deals. - Proven net-new experience selling complex technical products in fast-moving environments. - Strong sales fundamentals across discovery, multi-threading, champion-building, and deal momentum. - Genuine curiosity for open-source models and the AI infrastructure landscape. You follow model releases and can hold your own with engineers. - Highly dynamic: comfortable when a deal goes off-script, able to meet customers where they are, and willing to change your approach without losing rigor. - Strong technical project management: you can run a thorough evaluation across multiple workstreams and create clarity and direction for Baseten to win.. - Proven ability to sell internally, earning engineering time, aligning leadership, and getting cross-functional teams to move - Scrappy, low-ego, collaborative operator. You run toward ambiguous problems, create structure where none exists, and earn internal support without relying on rigid swim lanes. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: London Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re hiring a Founding Sales Leader in EMEA to build our business in the region from the ground up. We already have EMEA customers and real demand — today it’s served from the US. You’ll be our first person on the ground in London, and your job is to localize that business and turn it into a region. This is a founding-leader role, not inheriting a machine. You’ll be in deals directly while making your first hires, with a mandate to scale the EMEA team to 20+ people this year across front-line leaders and sellers. The right person for this role is a player-coach who has managed managers, sold to technical buyers, and hired quickly — and who wants to run a region before a bigger company would hand them one. If you’re energized by ambiguity, an unformed market, and building with what’s in front of you, this is one of the most consequential GTM roles at Baseten. RESPONSIBILITIES - Own EMEA: all segments, all markets, top to bottom. - Build the team. Recruit, hire, and onboard 20+ people this year, including the front-line leaders who will run it with you. - Carry the number. Build pipeline, run deals, and close business yourself while the team is coming together. - Establish our presence in the region — the London footprint, our reputation with EMEA buyers, and the local playbook for how enterprise buying works here. - Adapt the motion. Take what works in AMER and tune it to how technical buyers in EMEA actually evaluate and purchase infrastructure. - Partner closely with a US-based org across Sales, Marketing, Revenue Operations, Solutions, and Recruiting, with significant US timezone overlap. - Set the bar for execution, forecasting rigor, and speed as the region scales. REQUIREMENTS - A proven hiring track record. You’ve built teams quickly and hired leaders, not just ICs, and you can point to the people you’ve developed. - Second-line leadership experience. You’ve managed managers and owned a multi-team org. - Enterprise selling experience against a technical line of business. You can hold your own with engineering and infrastructure buyers and want to go deeper on inference. - Scrappiness. You’re comfortable being the only Baseten person in the region on day one — building pipeline, closing deals, and recruiting at the same time, without the bells and whistles. - EMEA fluency. You know the regional markets and how enterprise buying differs from the US. - Comfort in a fast-moving, high-intensity environment. Here, that means you Slack faster than you talk. - A builder’s mentality. You own problems and their solutions, and you’re at your best in high-change, unstructured environments.   BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: London Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Enterprise at Baseten means the companies with the most to gain from AI and the most complexity in getting there: large digital natives running products at massive scale, and category leaders in software, financial services, healthcare, and beyond. They have the data, the distribution, and the budget. Most are still deciding what to build, what to run themselves, and what it should cost. That makes this a consultative sale. You'll spend as much time helping a VP of Engineering pressure-test their AI strategy as you will selling against an alternative, mapping use cases, framing build-vs-buy, and giving clear recommendations grounded in what you've seen work at the frontier. Then you'll do the enterprise work: multithreading across a buying committee, navigating security and procurement, and turning a first workload into an eight-figure relationship. You'll work alongside our founders, forward-deployed engineers, and GTM leadership, in a seat where the playbook is still being written. RESPONSIBILITIES - Own a revenue target end to end, from prospecting and outbounding through closing Tier 1 accounts in your verticals - Act as a strategic advisor on AI adoption: identify use cases, shape architecture decisions, and lead with clear, opinionated recommendations - Multithread across large organizations, from the engineers running evals to the executives funding the program to security, legal, and procurement - Win lighthouse customers that become references for their entire industry - Partner with forward-deployed engineering on technical evaluations, POCs, and architecture reviews - Feed signal back to product and engineering. What enterprises need next is a roadmap input we don't get anywhere else REQUIREMENTS - 8+ years of enterprise B2B sales experience in technology, ideally infrastructure, API/platform, or developer tooling - A track record of closing seven- and eight-figure deals by navigating multi-stakeholder buying committees and long, complex cycles - Demonstrated ability to run a consultative sale. You've helped customers define a strategy, not just evaluate a product - Strong technical acumen: you can hold your own on model serving, GPU infrastructure, latency, and API architecture - Experience selling into large digital natives or regulated industries (financial services, healthcare/life sciences, insurance, government) - Excellent communication and comfort with high autonomy in a fast-moving environment NICE TO HAVE - Direct experience selling AI/ML infrastructure, cloud compute, or model deployment platforms BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: London Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're hiring a Sales Manager to help build and lead our founding team of Strategic Account Executives in London. Strategic at Baseten means the fastest-growing AI-native companies in the world, teams scaling from first inference call to billions of tokens in months. This is our fastest-growing segment, and Europe is where we're planting the flag next. You'll help recruit the first reps, run deals alongside them while the team ramps, and contribute to the playbook for how Baseten wins in Europe. It's a founding seat with real influence on how we build here, close to our founders and GTM leadership. RESPONSIBILITIES - Recruit, hire, and ramp the founding team of Strategic AEs in London. This is your highest-leverage work in year one - Coach reps to consistently exceed pipeline and revenue goals, with a hands-on approach through complex technical deals - Partner on shaping and executing go-to-market strategy for the region - Operate as a player-coach early on, carrying deals yourself while the team builds - Stay deep on the product and the open-source model landscape so your reps can hold their own with founders and engineering leaders - Work with Marketing, Product, and Engineering to turn European customer needs into roadmap input - Build a culture of accountability, learning, and collaboration from the first hire forward REQUIREMENTS - 6+ years of closing experience, with 2+ years managing high-performing teams - Proven success in Strategic or Enterprise sales, closing complex, multi-stakeholder technical deals - A track record of recruiting strong sellers, ideally as a first or early hire in a new team or region - Strong technical acumen, ideally in AI infrastructure, cloud infrastructure, or developer platforms. You're comfortable in the weeds - Willingness to sell as well as manage while the team is small - Based in London and able to be in office at least 3 days per week (Tuesday to Thursday) BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: London Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're hiring a Sales Manager to help build and lead our founding team of Enterprise Account Executives in London. Enterprise at Baseten means the companies with the most to gain from AI and the most complexity in getting there: large digital natives running products at massive scale, and category leaders in software, financial services, healthcare, and beyond. They have the data, the distribution, and the budget. Most are still deciding what to build, what to run themselves, and what it should cost. You'll help recruit the first reps, run deals alongside them while the team ramps, and contribute to the playbook for how Baseten wins European enterprises. It's a founding seat with real influence on how we build here, close to our founders and GTM leadership. RESPONSIBILITIES - Recruit, hire, and ramp the founding team of Enterprise AEs in London. This is your highest-leverage work in year one - Coach reps through long, multi-stakeholder cycles: multithreading across buying committees, navigating security and procurement, and closing seven- and eight-figure deals - Raise the bar on consultative selling. Your reps should be advising customers on AI strategy, not just running a product evaluation - Partner on shaping and executing go-to-market strategy for the region, including which verticals to attack first - Operate as a player-coach early on, carrying deals yourself while the team builds - Stay deep enough on the product to guide reps through technical evaluations, POCs, and architecture reviews alongside our forward-deployed engineers - Work with Marketing, Product, Engineering, and Legal to turn European enterprise requirements into roadmap and GTM input - Build a culture of accountability, learning, and collaboration from the first hire forward REQUIREMENTS - 6+ years of closing experience, with 2+ years managing high-performing teams - Proven success in Enterprise sales, closing complex, multi-stakeholder deals inside large organizations - Experience selling into large digital natives or regulated industries (financial services, healthcare/life sciences, insurance, government) - A track record of recruiting strong sellers, ideally as a first or early hire in a new team or region - Strong technical acumen, ideally in AI infrastructure, cloud infrastructure, or developer platforms. You're comfortable in the weeds - Willingness to sell as well as manage while the team is small - Based in London and able to be in office at least 3 days per week (Tuesday to Thursday) BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Our Sales and Solutions teams navigate hard technical conversations spanning inference performance, GPU economics, latency budgets, deployment shape. As Baseten’s platform matures, we need a dedicated owner to translate launch velocity into field readiness. As our first Product Enablement Lead, you'll sit between Product, Marketing, and Sales GTM and own how Baseten's products, features, campaigns, and market moments like the launch of GLM-5.2 https://www.baseten.co/blog/how-we-built-the-worlds-fastest-api-for-glm-52/ or Kimi K3 https://www.baseten.co/blog/making-kimi-k3-tokenization-18x-faster-for-million-token-agentic-workloads/ or the sudden evolution of Tokenomics https://newsletter.semianalysis.com/p/tokenbudgeting-our-conversations as a discipline get translated into field execution. You will own how these launches land with the field, how AEs and SAs stay credible on a highly dynamic technical ecosystem, and how what the field hears from customers makes it back to Product. This is a hands-on individual contributor role. You are the bridge between product, marketing, and sales. You'll build the system and run it, which includes cross-functional program leadership, direct training and enablement of in-seat reps, and content and curriculum development for managers, sellers, and new hires. Success here will depend on your ability to build repeatable systems and rhythms and to partner across the business and with your enablement colleagues to ensure alignment and speed of execution. RESPONSIBILITIES - Own launch readiness: partner with Product and Marketing on positioning, write internal launch comms, and run readiness sessions so AEs and SAs can sell new products on day one. - Build and deliver technical enablement that makes the field credible on inference, GPUs, latency, and deployment. Raise the floor for AEs; give SAs the depth they need. - Produce the customer-facing collateral that comes out of this work: decks, battlecards, and demos that hold up in front of an engineer. - Build repeatable systems, not just content, so enablement keeps pace with the product roadmap. - Own the Product Feedback system from customers and the field back to Product and Marketing. Help identify what is resonating with customers and what isn't, in order to shape positioning, packaging, and roadmap. - Define and report on how we know enablement is working (ramp time, adoption of new products in deals, win rate on launches). REQUIREMENTS - 5+ years in product enablement, GTM enablement, field enablement, or product marketing at an infrastructure, developer tools, or AI-native company. - Experience enabling an internal sales field (AEs, SAs), as opposed to onboarding customers' engineers. - Technical depth: a CS or engineering background, prior SE/SA experience, or a track record of building demos and technical content yourself. You can hold your own in a conversation about model serving. - Hands-on track record. You have personally written the collateral and run the sessions, and can point to programs, talks, docs, or certifications you built. - Systems mindset: you think in repeatable workflows, not one-off deliverables, and you're comfortable defining success and measuring it. - Comfortable operating in ambiguity as the first hire in a function. - You actively use AI tools to drive your own productivity - in how you draft content, translate technical detail for different audiences, and accelerate your work. - Based in the SF Bay Area or willing to relocate. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: San Francisco, CA • New York, NY Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma’s Data Science team partners across product, engineering, design, marketing, sales, and operations to help Figma make better decisions with data.  As an intern on our team, you'll work on technical challenges that have real impact on our product and business, and we're looking for interns with strong foundations in coding and statistics and  who are clear communicators with both technical and non-technical audiences. This internship will be based out of our San Francisco or New York Hub. What you'll do at Figma: Own a scoped project end to end—from framing the question with Product, Engineering, Design, and Data Science partners through delivering the work—with support from a manager and mentor. Analyze user behavior, product performance, or business data to uncover insights and translate them into recommendations for businessDesign and evaluate experiments and develop metrics that help teams understand the impact of product changes.Build models to understand user behavior and predict growth Build and improve  data pipelines and tools that make product data more scalable and accessible Focus areas may include analytics, experimentation, or infrastructure - based on your interests  and business needs Some projects you could work on: Analyze how people adopt and use a new or existing Figma product experience, define meaningful success metrics, and turn patterns in engagement and retention into product recommendations. Build and validate a new analytical method or tool that expands how Figma’s Data Science team solves recurring problems. Study marketing or customer-journey data to identify drivers of acquisition, conversion, or retention. Develop and evaluate forecasts or models that help teams anticipate user or business trends and plan more effectively We'd love to hear from you if you have: Experience using SQL and a scripting language such as Python or R to clean, explore, and analyze data through research, projects, or prior work. A solid foundation in statistics and quantitative reasoning, with exposure to areas such as experimentation, forecasting, statistical modeling, causal inference, or data modeling. The ability to structure open-ended questions, validate your analysis, and connect findings to product or business decisions. Curiosity, initiative, and strong communication and collaboration skills with both technical and non-technical partners. At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Pay Transparency Disclosure This internship role is based in either Figma’s San Francisco or New York hub offices, and has the hourly base pay rate stated below.  Figma also offers interns a housing stipend and travel reimbursement. Figma’s compensation and benefits are subject to change and may be modified in the future. Internship $46 — $46 USD At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status , or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com . These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities. Examples of accommodations include but are not limited to: Holding interviews in an accessible location Enabling closed captioning on video conferencing Ensuring all written communication be compatible with screen readers Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice . Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles: Candidates may submit up to 5 applications during any rolling 30-day period. Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection. Once the applicable days has passed, candidates are welcome to apply again.

Задачи: — Проектировать и разрабатывать multi-agent системы. — Интегрировать LLM с внутренними инструментами и сервисами. — Разрабатывать backend-сервисы и API для agent workflows. — Реализовывать RAG pipelines и tool/function calling. — Создавать CLI-based agent workflows и инструменты автоматизации. — Разрабатывать Computer Vision pipelines: object detection, multi-object tracking, person re-identification. — Разрабатывать multi-camera multi-person tracking для сетей камер. — Работать с видеопотоками в реальном времени и оптимизировать GPU inference. Требования: — Опыт работы с Node.js ecosystem и Express.js. — Уверенное владение Python. — Опыт работы с LLM APIs и prompt engineering. — Опыт работы с RAG, tool calling или agent frameworks. — Знакомство с Docker, Linux и Git. — Опыт работы с PyTorch и OpenCV. — Опыт в object detection и multi-object tracking. — Опыт работы с YOLO, ByteTrack / BoT-SORT или аналогами. — Понимание person re-identification и vector search. — Опыт работы с Milvus / FAISS. — Опыт обработки видео с ffmpeg / GStreamer. — Работа с RTSP и hardware decoding. Будет плюсом: — Опыт в NLP и ML. — Опыт развёртывания open-source LLM. — Опыт оптимизации inference. — Опыт работы с Vision-Language Models. — TensorRT / ONNX Runtime. Условия: — Удалённый формат работы. — Заработная плата: 1.600–3.200 USD net в месяц.

1 600 – 3 200 $

Задачи: — разработка и развитие LLM-проектов в юридическом домене — от прототипов до продакшена — проектирование и обучение агентов-экспертов, решающих задачи правового домена (RAG-пайплайны, классификация запросов, генерация ответов, оценка релевантности) — исследование и настройка multi-agent orchestration (LangGraph, LangChain, schema guided reasoning pipelines) — работа с GigaChat как основной моделью, а также эксперименты с ChatGPT, Gemini, Qwen — дообучение малых моделей (instruction-tuning, adapters, LoRA) для повышения качества юридического рассуждения — разработка метрик качества — взаимодействие с инженерами и аналитиками права — внедрение моделей в реальные кейсы (алиментные, потребительские, трудовые и т.д.) Требования: — опыт работы DS/ML-инженером от 3х лет — понимание архитектуры LLM и принципов prompt engineering — опыт построения RAG-систем, fine-tuning и дообучения моделей — умение проектировать пайплайны inference / retraining Будет плюсом: — опыт в LegalTech или смежных областях (финансы, документооборот, чат-боты) — понимание структуры и логики российских нормативных актов — опыт интеграции LLM с внешними API или базами знаний Условия: — формат работы офис на испытательном сроке, локация офиса ул Вавилова д.19 — ежегодный пересмотр зарплаты, годовая премия — корпоративный спортзал и зоны отдыха — более 400 образовательных программ СберУниверситета для профессионального и карьерного развития — расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа — гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ — подписка Прайм с возможностью совместного использования на трёх близких — вознаграждение за рекомендацию друзей в команду Сбера.

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Требования: • Агентная разработка (vibe coding) • Опыт продуктовой разработки от 4 лет, уровень senior fullstack • Агентные CLI-инструменты (Claude Code, Codex CLI, Cursor agent mode, Aider) как основной способ работы • Spec-driven development: формулирование функциональных и нефункциональных требований до первого промпта; умение писать инженерные спецификации и контекстные файлы (правила, схемы, markdown) • Модульность: слабая связанность, доменные границы, нарезка проекта на небольшие изолированные файлы • Управление контекстным окном для предотвращения дрейфа и галлюцинаций • Умение сбросить сессию агента и начать заново с более жёсткими ограничениями • Разработка в несколько потоков, менеджмент репозитория под агентную работу, опыт коллаборативной AI-разработки • Ревью и аудит AI-кода: слабые имена, дублирование, отсутствующие проверки, небезопасная работа с данными • Тесты как способ управления агентом: юнит- и интеграционные тесты пишутся до логики фичи • Инфраструктура и восстановление: версионирование, снапшоты БД, бэкапы, CI, процедуры восстановления данных • Готовность писать код руками при необходимости и ответственность за результат, включая код, сгенерированный агентом • Современный типизированный backend-язык с асинхронностью, моделью ошибок, управлением зависимостями, воспроизводимым окружением • HTTP API и realtime-транспорт: REST, двусторонние соединения, стриминг, протокол сообщений, переподключения, валидация схем • Автотесты: юнит- и интеграционные, изоляция внешних сервисов и зависимостей, поддержание тестовых данных • Реляционные БД: схема, миграции, индексы, нетривиальные запросы, понимание пределов БД • Разрешение конфликтов зависимостей, включая бинарную несовместимость библиотек • Компонентный SPA-фреймворк и типизированный JavaScript; готовность сменить фреймворк за неделю • Компонентные тесты в браузерном окружении • Realtime-клиент: переподключения, стриминг, рантайм-валидация сообщений • Медиа в браузере: доступ к устройствам ввода, работа с аудиопотоком, кодирование и передача • Состояние на клиенте и ограничения браузера: защищённый контекст, сертификаты в dev, хранилище • Умеренность в UI: простой интерфейс без тяжёлых фреймворков и дизайн-систем • Классические CV-задачи: детекция, эмбеддинги, кластеризация, обработка изображений и метаданных, дедупликация • Локальные LLM: форматы весов и квантизации, размер контекста, латентность, стоимость запроса; умение измерять • Речевые модели: распознавание и синтез речи, баланс качества и ресурсов, ограничения по задержке и длине входа • Мультимодальные модели: генерация описаний по изображению, оценка качества генерации • Эмбеддинги и векторный поиск: семантический поиск, гибридные схемы, переранжирование, метрики качества • Ресурсы и эксплуатация inference: одна модель на процесс, память ускорителя, батчинг, прогрев, поведение под нагрузкой • Не требуется: обучение моделей с нуля, MLOps, распределённое обучение • Пайплайны обработки как идемпотентные стадии с фиксацией состояния • Понимание разницы между инкрементальным и полным пересчётом и цены ошибки • Целостность данных при деплое, сведение расходящихся баз, миграции данных • Границы сервисов: процессы, владение данными, поведение при отказах • Контейнеризация: образы с тяжёлыми зависимостями, тома для данных и весов моделей, политики перезапуска, диагностика падений • Linux и сеть: удалённый доступ, проброс портов, разрешение конфликтов, чтение логов • Скриптование рутины: деплой, синхронизация данных, ротация логов • Уверенное владение Git, включая нетривиальные операции; чтение истории • Базовая безопасность: сервис без аутентификации локален, секреты не в репозитории, dev/prod режимы разведены • Автоматические smoke-проверки интерфейса после изменений • 4+ года разработки, из них 2+ года бэкенда в продакшене • 1+ год реального фуллстека: разработка клиента и сервера • Проект с LLM/ML как частью продукта • Запуск моделей локально или on-premise • 2–3+ месяца ежедневной работы через агентные инструменты Задачи: • Подключение и настройка USB-камеры: интеграция с ПО, захват видеопотока, детекция лиц, распознавание жестов • Реализация стереоскопического режима 2D→3D на телевизоре без специализированной 3D-панели • Разработка клиентских интерфейсов для телевизора и мобильного устройства по дизайн-макетам, адаптация вёрстки, интеграция с бэкендом, двустороннее realtime-взаимодействие • Разработка технической документации, инженерных спецификаций и контекстных файлов, используемых при агентной разработке

Требования: • Агентная разработка (vibe coding) • Опыт продуктовой разработки от 4 лет, уровень senior fullstack • Агентные CLI-инструменты (Claude Code, Codex CLI, Cursor agent mode, Aider) как основной способ работы — поставленные и поддерживаемые продуктовые фичи, а не прототипы; ключевым является методика, а не знание конкретного инструмента • Spec-driven development: функциональные и нефункциональные требования формулируются до первого промпта; спецификация → план → код; умение писать инженерные спецификации и контекстные файлы (правила, схемы, markdown), удерживающие агента в рамках задачи • Модульность как условие агентной работы: слабая связанность и доменные границы, нарезка проекта на небольшие изолированные файлы вместо монолита • Управление контекстным окном: осознанный подбор того, что попадает в контекст, для предотвращения дрейфа и галлюцинаций на устаревшем коде • Умение вовремя сбросить сессию: остановить зациклившегося агента, очистить рабочее дерево и начать заново с более жёсткими ограничениями • Разработка в несколько потоков, менеджмент репозитория под агентную работу, опыт коллаборативной AI-разработки • Ревью и аудит AI-кода: слабые имена, дублирование, отсутствующие проверки, небезопасная работа с данными • Тесты как способ управления агентом: осмысленные юнит- и интеграционные тесты пишутся до логики фичи • Инфраструктура и восстановление: версионирование, снапшоты БД, бэкапы, CI, готовая процедура восстановления данных • Готовность писать код руками, когда агент упёрся, и ответственность за результат, включая код, сгенерированный агентом • Современный типизированный backend-язык: асинхронность, модель ошибок, управление зависимостями, воспроизводимое окружение • HTTP API и realtime-транспорт: REST и двусторонние соединения — стриминг, протокол сообщений, переподключения, валидация схем на границе • Автотесты как норма: юнит- и интеграционные, изоляция внешних сервисов и тяжёлых зависимостей, поддержание тестовых данных • Реляционные БД руками: схема, миграции, индексы, нетривиальные запросы, понимание пределов выбранной БД • Разрешение конфликтов зависимостей, включая бинарную несовместимость библиотек (характерно для окружений с ML-пакетами) • Компонентный SPA-фреймворк и типизированный JavaScript; конкретный фреймворк не принципиален, принципиальна готовность сменить его за неделю • Компонентные тесты в браузерном окружении, а не только ручная проверка • Realtime-клиент: переподключения, стриминг, рантайм-валидация входящих сообщений • Медиа в браузере: доступ к устройствам ввода, работа с аудиопотоком, кодирование и передача • Состояние на клиенте и ограничения браузера: защищённый контекст, сертификаты в dev, хранилище • Умеренность в UI: простой интерфейс без тяжёлых фреймворков и дизайн-систем • Классические CV-задачи: детекция, эмбеддинги и кластеризация объектов, обработка изображений и метаданных, дедупликация • Локальные LLM: форматы весов и квантизации, размер контекста, латентность и стоимость запроса; умение измерять, а не предполагать • Речевые модели: распознавание и синтез речи, размен качества на ресурсы, ограничения по задержке и длине входа • Мультимодальные модели: генерация описаний по изображению, оценка качества генерации • Эмбеддинги и векторный поиск: семантический поиск, гибридные схемы с полнотекстовым, переранжирование, метрики качества выдачи • Ресурсы и эксплуатация inference: одна модель на процесс, память ускорителя, батчинг, прогрев, поведение под нагрузкой • Не требуется: обучение моделей с нуля, MLOps-платформы, распределённое обучение • Пайплайны обработки как идемпотентные стадии с фиксацией состояния: перезапускаемость, докат, инкрементальность • Понимание разницы между инкрементальным и полным пересчётом и цены ошибки (полный пересчёт обычно уничтожает ручную разметку) • Целостность данных при деплое, сведение расходящихся баз, миграции данных, а не только схемы • Границы сервисов: как процессы общаются, кто владеет данными, что происходит при отказе одного из них • Контейнеризация: образы с тяжёлыми зависимостями, тома для данных и весов моделей, политики перезапуска, диагностика падений • Linux и сеть: удалённый доступ, проброс портов, разрешение конфликтов портов, чтение логов как основной способ разбирательства • Скриптование рутины: деплой, синхронизация данных, ротация логов • Уверенное владение Git, включая нетривиальные операции; чтение истории как источника проектных решений • Базовая безопасность: сервис без аутентификации не выходит за пределы локального интерфейса, секреты не попадают в репозиторий, dev- и prod-режимы разведены явно • Автоматические smoke-проверки интерфейса после изменений • 4+ года разработки, из них 2+ года бэкенда в продакшене • 1+ год реального фуллстека: разработка и клиента, и сервера к нему • Проект, где LLM/ML были частью продукта, а не демонстрационным примером • Запуск моделей локально или on-premise, а не только вызовы облачных API • 2–3+ месяца ежедневной работы через агентные инструменты Задачи: • Подключение и настройка USB-камеры на целевом устройстве: интеграция камеры с ПО устройства и захват видеопотока; детекция лиц и определение пользователя, находящегося перед устройством; распознавание управляющих жестов • Реализация стереоскопического режима 2D→3D: поиск и реализация способа вывода стереоскопического изображения на произвольном телевизоре, не требующем специализированной 3D-панели (приоритетный вариант — пассивное 3D) • Разработка клиентских интерфейсов для телевизора и мобильного устройства: реализация экранов по предоставляемым Заказчиком дизайн-макетам; адаптация вёрстки под особенности вывода на телевизоре и под мобильные экраны; интеграция с существующим бэкендом Заказчика, включая двустороннее realtime-взаимодействие • Разработка технической документации по всем перечисленным блокам работ, включая инженерные спецификации и контекстные файлы, использованные при агентной разработке

Location: SF or Remote (US/Canada) At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. APPLYING TO RENDER We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, and we value the candidate experience just as much as our customer experience. We hope your conversations with us reflect a thoughtful process that is illuminative, enjoyable, and respectful of your time. ABOUT THE ROLE We are looking for Render's first Forward Deployed Engineer to work hands-on with our most strategic customers. Our largest contracts and fastest-growing AI startups are scaling on Render, and this role provides them with a dedicated, concierge-level technical partnership. You will balance two motions: white-glove engagement with our top accounts, where you work closely with the customer's engineering team as a trusted technical partner, and scoped onboarding intensives that get high-growth startups confidently building on the platform. As the first FDE in our Field Engineering organization, you will define the playbook for this function, prove the model, and shape how it scales. WHAT YOU'LL DO - Work closely with Render's top accounts as their dedicated technical partner, providing concierge service across architecture reviews, migration planning, and hands-on delivery. - Run scoped onboarding intensives for high-growth startups, from intake and success criteria through hands-on-keyboard execution. - Lead the database side of customer engagements, including Postgres architecture, performance tuning, and complex data migrations from Heroku, AWS, and other cloud providers. - Drive activation and expansion in strategic accounts: turn major credit grants into durable production adoption, surface expansion signals from your technical work, and partner with the account team to convert them into revenue. - Own the ongoing technical relationship for your accounts: proactive architecture and health reviews, collaborative roadmap sessions, incident follow-up and RCA, and escalation point for hard technical problems, working closely with the account team. - Build the FDE playbook: qualification criteria, engagement templates, success metrics, and reference architectures that make the program repeatable. - Act as a high-signal feedback channel to product and engineering, translating customer friction into prioritized product input. - Partner with Account Managers and Customer Engineers to ensure smooth handoffs after each engagement and durable long-term coverage. WHAT WE'RE LOOKING FOR - 8+ years in a hands-on, customer-facing engineering role: forward deployed, solutions, customer, or professional services engineering. - Strong software engineering fundamentals; you can write production-quality code and work hands-on-keyboard inside a customer's codebase. - Deep experience with cloud infrastructure: containers, CI/CD, networking, autoscaling, and running real workloads in production. - Deep Postgres and database expertise: schema design, performance tuning, replication, and production data migrations. Our largest engagements consistently turn on this skill set. - AI fluency: you work with AI tools daily to accelerate your own delivery, and you understand LLM application architectures well enough to guide the teams building them. - Excellent communication with everyone from startup founders to enterprise platform teams, including executive-level conversations. - Self-directed and comfortable with ambiguity; you can stand up a new function without an existing playbook. - Commercial instincts: you understand how technical wins connect to expansion, renewal, and revenue. NICE-TO-HAVES - Migration experience from Heroku, AWS, or other clouds onto modern platforms. - Hands-on experience shipping AI and LLM applications (RAG pipelines, agent frameworks, inference workloads); many of our fastest-growing accounts are AI-native. - Prior experience as the first hire in a role or a founding member of a new program. If this role excites you but you don’t meet every single requirement, we’d still love to hear from you—your unique experience might be just what we need. BENEFITS - 4 weeks of paid vacation. - 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child. We will also work with you to create a supportive plan of return. - Long-term disability, life insurance, and 401K plans. - 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent. FSAs and HSAs are available as well. - Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc. - Monthly cell phone and internet subsidy. - Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders. - Continuous learning benefits & related support. This position is generally not eligible for new visa sponsorship. At Render's discretion, the business may sponsor existing visa transfers. Applicants who require sponsorship must receive business authorization. Render is an equal-opportunity employer. We know that employing a team rich in diverse thoughts, experiences, and opinions allows our employees, product, and community to flourish. We make all employment decisions including hiring, evaluation, termination, promotional, and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. We encourage all who are interested to apply. We can't wait to hear from you! Render — CCPA Applicant Privacy Notice https://drive.google.com/file/d/1wKr9IejoT5McFrs9I2mahQnf6AFwb3z2/view Render — GDPR Applicant Privacy Notice https://drive.google.com/file/d/1_8jtyXQ1HdRdTdQn9sZ7n-R-zAGBmsFa/view

Location: Hybrid - San Francisco About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About The Role: Vercel is hiring a Strategic Product Partnerships Lead to develop first-of-a-kind partnerships that inflect the company's growth. Done well, these partnerships open distribution for our products, create new pipeline for our field teams, and/or add new capabilities to our platform. This is a highly cross-functional and technical role: you will spend as much time with product and engineering leaders as with commercial ones, both with partners and with Vercelians. You will report to the Head of Strategic Partnerships and own a named set of partners that includes hyperscalers, frontier AI labs, silicon vendors, and commerce and enterprise software platforms. The work takes a different shape with each one, but the common thread is that these partnerships live close to the product: embedding Vercel inside a partner's platform, co-building new products, taking a joint offering to enterprises that neither company could sell alone. Structuring a deal means both understanding the technical components well enough to know what a partnership makes possible and understanding what the business impact could be if done successfully. We expect candidates to demonstrate significant experience delivering complex deal work, creating and driving strategy, working with cross-functional teams to launch new initiatives, and initiating first-of-a-kind partnerships. We are looking for someone with a strong sense of ownership who performs at a senior level and does their best work with limited direction. This is a hybrid position, requiring 3 days per week in one of our San Francisco, Austin, or New York City offices. What You Will Do: Own a named set of strategic partners end to end, from first conversation through signed agreement to launch and growth Identify and develop new partnerships with the companies that matter most to Vercel's strategy across AI, cloud, commerce, and enterprise software Build the business case: size the opportunity, scope the product and engineering investment it requires, and give leadership a clear recommendation, including when the recommendation is to pass Lead negotiations end to end, structuring commercial agreements that are new to Vercel and often new to the partner: revenue share, embedded pricing, co-sell commitments, marketplace terms Develop senior relationships on the partner side and bring Vercel executives in where the relationship calls for it Lead cross-functional teams across Product, Engineering, Sales, Marketing, Finance, and Legal to take a signed agreement to launch Advise Vercel leadership on where the ecosystem is moving and what it means for our roadmap Run deals with structure: clear milestones, agreed measures of success on both sides, and the judgment to stop the ones that are not working About You: 8+ years developing, negotiating, and executing complex commercial agreements, ideally at a platform, infrastructure, cloud, or developer tools company A track record of initiating partnerships that had no precedent, with companies significantly larger than your own. You can walk through the terms you won and the ones you gave up Experience structuring deals with significant technical surface area: platform integrations, embedded or whitelabeled product, licensing, infrastructure and compute commitments. You can hold a credible conversation with a partner's product and engineering teams about agents, inference, model routing, and cloud infrastructure Experience creating and driving strategy, and getting an organization to fund it Comfortable leading cross-functional teams you do not manage, through Product, Engineering, Legal, Finance, and Sales Strong agency and comfort with ambiguity. You decide what to work on and can defend the choice Speed. You move quickly and decisively, and you keep large deals from stalling Excellent written and verbal communication with executives on both sides of the table Bonus if you: Have done partnerships at or with a hyperscaler, a frontier AI lab, or a large commerce or enterprise software platform Have structured technology licensing, OEM, or embedded distribution agreements Started in a technical role (engineering, solutions architecture, or technical product) before moving into commercial work Compensation & Benefits: Competitive compensation package, including equity. Inclusive Healthcare Package. Learn and Grow - we provide mentorship and send you to events that help you build your network and skills. Flexible Time Off. We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed. The San Francisco, CA salary range for this role is $194,000 - $237,000, plus an annual company target bonus. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location. The total compensation package may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program depending on the role. Your recruiter can share more details during the hiring process. Disclosures: Privacy: Please review our Job Applicant Privacy Policy for more information on how we handle your data. Equal Opportunity: Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.

Компания МТС Банк ищет специалиста на позицию ML/DevOps Engineer в Москве. Задачи: — деплоить и интегрировать модели, сопутствующие сервисы и инструменты, автоматизировать поставку и оптимизировать потребление ресурсов — мониторить и поддерживать работоспособность — обеспечивать соответствие политикам информационной безопасности и стандартам надёжности при развёртывании ML‑решений Требования: — уверенное администрирование Linux, понимание сетевых протоколов и потенциальных точек отказа — опыт конфигурации и распределения мощностей видеокарт для обучения и инференса моделей — опыт настройки мониторинга инфраструктуры и метрик деградации моделей — опыт работы с vllm, Triton Inference Server, FastAPI, KServe или TorchServe — опыт построения сложных многоэтапных пайплайнов с упором на безопасность Технологический стек включает Docker, Linux, Kubernetes, Bash, GitLab CI, Ansible, Terraform, Airflow, Python, vllm, cuda, triton, Prometheus/Victoria Metrics, Grafana, SQL, Postgres, Elasticsearch, MLflow, Qdrant, Nexus, Vault.

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Задачи: — Разработка и внедрение агентов на базе LLM, проектирование ML-компонентов платформы агентов. — Создание агентов, способных обрабатывать сложные multi-turn и multi-modal запросы пользователей. — Разработка систем маршрутизации задач, выбора инструментов и моделей, управление вызовами функций и оркестрация моделей внутри пайплайна. — Замена традиционных классификаторов LLM-пайплайнами и RAG-системами, трансформация старых архитектур в современные пайплайны с LLM, вызовом функций, планированием и рассуждениями. — Дообучение, настройка и интеграция моделей, оптимизация inference, работа с опенсорс-моделями и внутренними, включая fine-tuning, RL и адаптацию под платформу агентов. — Обеспечение быстрой и устойчивой работы агентов на продакшене, оптимизация inference и взаимодействие с инфраструктурой (Eagle, FP8, дистилляция, multi-dimensional parallelism). — Исследования и эксперименты с графами агентов и памятью, эксперименты с вызовами агентов, memory-подсистемами, симуляцией поведения, архитектурами reasoning и системами планирования. — Участие в разработке RL-моделей для обучения диалоговых агентов, постановка и реализация экспериментов с multi-turn reinforcement learning в масштабах Яндекса и Алисы. Требования: — Глубокие знания в Deep Learning и NLP. — Опыт работы с LLM и пайплайнами вокруг них (function calling, memory, RAG). — Опыт внедрения ML-систем в продакшен. — Системное мышление — от архитектуры до интеграции с инфраструктурой. — Владение Python и знакомство с PyTorch. — Готовность к кросс-функциональной работе с бэкендом и продуктовыми командами.

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