Разработка вакансии - гибрид

Location: San Francisco; Toronto; New York; Montreal; Seattle 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 looking for distributed systems engineers and product-minded generalists to build the distributed runtime that powers large-scale LLM inference on Baseten. Our inference platform empowers customers to deploy and operate cutting-edge models with industry-leading performance, scalability, and reliability. It also powers Model APIs, our hosted endpoints for the latest open-source models. You'll work across the stack, from the developer experience customers use to deploy models, through the libraries behind features like tool calling and reasoning, down to the systems that orchestrate deployments on Kubernetes and route traffic efficiently. Your job is to make sure every model on our platform is fast, reliable, and cost-efficient. You'll join a small, high-impact team at the intersection of distributed systems, model performance, infrastructure, and product, helping define how developers use AI models at scale. This role is ideal for engineers who enjoy owning systems in production, solving hard integration problems, and making complex infrastructure simple and reliable for users.   EXAMPLE INITIATIVES You'll get to work on these types of projects on our Inference Platform: - The Baseten Inference Stack at NVIDIA Dynamo Day https://www.baseten.co/blog/nvidia-dynamo-day-baseten-inference-stack/ - 2x faster inference with KV cache-aware routing https://www.baseten.co/blog/how-baseten-achieved-2x-faster-inference-with-nvidia-dynamo/ - How Baseten multi-cloud capacity management (MCM) unifies deployments https://www.baseten.co/blog/how-baseten-multi-cloud-capacity-management-mcm-powers-cloud-self-hosted-and-hybr/#comparing-deployment-options-cloud-vs-self-hosted-vs-hybrid RESPONSIBILITIES - Build the infrastructure and orchestration systems that deploy and run large-scale distributed LLM inference, including routing, autoscaling, scheduling, and runtime management. - Design, build, and operate Model APIs, with a focus on advanced inference capabilities: structured outputs (JSON mode, grammar-constrained generation), tool/function calling, and multimodal serving. - Implement platform fundamentals such as API versioning, validation, usage metering, quotas, and authentication. - Instrument deep observability (metrics, traces, logs) and build repeatable benchmarks for speed, reliability, and quality. Help set best practices for testing, release automation, and operational excellence. - Debug and harden complex production systems spanning Kubernetes, distributed runtimes, networking, and GPU workloads to improve reliability and scalability. - Partner with Inference Performance engineers and other teams to make new optimizations broadly available to customers and easy to configure. - Own projects end to end, from architecture through deployment, monitoring, and iteration on customer feedback. Along the way, make thoughtful tradeoffs between performance, reliability, operational simplicity, and developer experience.   REQUIREMENTS - Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, or a related field, or equivalent practical experience. - 3+ years building and operating distributed systems, backend infrastructure, or large-scale APIs where reliability, latency, and scale are first-class concerns. - A proven track record of owning low-latency, reliable backend services, including rate limiting, auth, quotas, metering, and migrations. - Infrastructure instincts with a feel for performance: profiling, tracing, capacity planning, and SLO management. - Comfort debugging performance and reliability issues across multiple layers of the stack, from application behavior down to runtime and infrastructure internals. - A strong sense of developer experience. You think about how systems are used, not just how they work. - Eagerness to learn new languages, frameworks, and systems, and a real interest in inference engineering. Prior ML or LLM experience isn't required, though experience with model serving or inference systems is a plus. - Excellent written communication and collaboration skills, including writing clear design docs and working across functions.   NICE TO HAVE - Experience with or contributions to LLM inference engines and frameworks such as vLLM, SGLang, TensorRT-LLM, TGI, or Dynamo. - Deep Kubernetes experience, including operators and custom resources, plus familiarity with service meshes or API gateways. - Experience with distributed scheduling, autoscaling, or service orchestration. - Experience operating GPU workloads in production. - A background in developer-facing infrastructure or APIs, or contributions to open-source infrastructure or ML systems. - Familiarity with observability tooling, CI/CD systems, or release automation. 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; Toronto; New York; Montreal; Seattle 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 looking for inference performance engineers who want to make the world's most demanding AI workloads run faster and more efficiently. You'll work across the stack, from the inference engine and runtime through scheduling, serving, and routing. Along the way you'll apply techniques like prefill/decode disaggregation, speculative decoding, and KV-cache management. You'll reason from first principles about where time and memory go, find what's holding performance back, and close the gap. Your work directly impacts how fast our customers' models run and how efficiently we serve them. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM inference.   EXAMPLE INITIATIVES You'll get to work on these types of projects as an Inference Performance engineer: - Agentic Kernels in Production https://www.baseten.co/blog/agentic-kernels-in-production/ - How we built the new fastest API for GLM-5.2 https://www.baseten.co/blog/how-we-built-the-new-fastest-api-for-glm-52/ - Live draft model training for speculative decoding https://www.baseten.co/blog/live-draft-model-training-for-speculative-decoding/#eliminating-traditional-bottlenecks - Making Kimi K3 Tokenization 18x faster https://www.baseten.co/blog/making-kimi-k3-tokenization-18x-faster-for-million-token-agentic-workloads/ - The Baseten Inference Stack https://www.baseten.co/resources/guide/the-baseten-inference-stack/ - Driving model performance optimization https://www.baseten.co/blog/driving-model-performance-optimization-2024-highlights/ RESPONSIBILITIES - Implement and productionize cutting-edge inference techniques, working deep in runtime internals. That includes quantization, speculative decoding, KV-cache reuse, chunked prefill, LoRA, guided generation for structured outputs, and custom scheduling and routing algorithms. - Profile and optimize inference end to end, from kernel launch overhead and memory layout up to request scheduling, prefill/decode disaggregation, and cache-aware routing. Run cross-layer investigations, such as tracing a tail-latency regression from request timing through routing and batching down to a kernel. - Turn performance into cost savings. Improve tokens per GPU-hour, raise utilization, and give customers and internal teams clear latency/throughput/cost tradeoffs. - Bring up and tune new model architectures on new hardware quickly, often in the same week they're released. - Build benchmarking frameworks that measure real-world performance across model architectures, batch sizes, sequence lengths, and hardware configurations. - Contribute upstream to open-source inference engines (vLLM, SGLang, TensorRT-LLM), and partner closely with model, infrastructure, and customer-facing teams to ship wins.   REQUIREMENTS - Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field. - Experience with one or more general-purpose programming languages, such as Python or C++. - Familiarity with LLM optimization techniques (e.g., quantization, speculative decoding, continuous batching). - Strong familiarity with ML libraries, especially PyTorch, TensorRT, or TensorRT-LLM. - Demonstrated interest and experience in LLMs. - Deep understanding of GPU architecture.   NICE TO HAVE - Proficiency in enhancing the performance of software systems, particularly in the context of large language models (LLMs) - Contributed to vLLM, SGLang, TensorRT-LLM, or another inference engine. - Worked on large-scale distributed serving: autoscaling, load balancing, multi-region or multi-cloud capacity. - Written or optimized GPU kernels (CUDA, Triton, CUTLASS, or similar) - Worked on quantization (FP8/FP4, AWQ, GPTQ) or speculative decoding in production. - Deep understanding of software engineering principles and a proven track record of developing and deploying AI/ML inference solutions. 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).

We're looking for a manager to own the performance of our Document Processing team and lead the Processing Supervisors who run it day to day. If you think in systems, lead through others, and measure what matters, this role is for you.

Задачи: — Оптимизация производительности — Написание тестов — Работа с внешними сервисами и API — Использование экосистемы .NET — Взаимодействие с разработчиками, аналитиками, тестировщиками и менеджерами проектов для согласованного процесса разработки — Освоение новых версий .NET и сопутствующих библиотек — Освоение требуемых IDE, LLM, AI инструментов — Улучшение знания смежных технологий, в том числе DevOps Требования: — Высшее техническое образование — Опыт работы в команде от 3 лет — Уверенное владение C# — .NET Core 8+ — Понимание и применение SOLID — Знание протокола HTTP — Опыт разработки WEB API — Опыт работы с микросервисной архитектурой — Понимание структур данных и алгоритмов — Работа с БД через Entity Framework — Знание SQL: умение писать сложные запросы — Unit, интеграционное тестирование — Уверенное использование Git — Опыт интеграции сторонних библиотек и SDK — Опыт использования AI инструментов в разработке Будет плюсом: — Full stack — React JS — PostgreSQL — Опыт построения CI/CD — Опыт использования подхода Spec Driven Development — Инструментальное владение AI для анализа, генерации и автоматизации Условия: — Комфортный современный офис в Москве (Варшавское шоссе, 25Астр6) — График работы – офис, гибрид после испытательного срока — Ежегодный пересмотр зарплаты, годовая премия — Корпоративный спортзал и зоны отдыха — Более 400 образовательных программ СберУниверситета для профессионального и карьерного развития — Расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа — Ипотека выгоднее до 7% для каждого сотрудника — Подписка Прайм с возможностью совместного использования на трёх близких — Вознаграждение за рекомендацию друзей в команду Сбера.

-Проектировать и разрабатывать масштабируемые микросервисы для высоконагруженных банковских систем. -Проектировать и оптимизировать сложные запросы к MS SQL Server (T-SQL), обеспечивая высокую производительность при работе с большими объемами данных.

🔵Разрабатывать и запускать бэкенд-фичи вместе с продуктовыми командами (мобайл, веб, маркетинг, аналитика). 🔵Подключать AI- и API-провайдеров и автоматизировать интеграции, чтобы новые подключения не требовали ручной работы.

🌸Work with our engineers and leverage your own knowledge to understand the challenges they face and how to improve their experience. 🌸Contribute to our internal development platform (IDP) by designing, implementing, and maintaining internal tooling and systems.

• Разрабатывать и улучшать высокопроизводительные C/C++ компоненты. • Создавать и оптимизировать low-level модули.

• Участвовать в пресейлах по финансовому контуру. • Участвовать в крупных проектах внедрения в составе проектной команды (от стадии анализа до запуска).

-Проектированием и разработкой внутренних библиотек и фреймворков. -Разработкой внутренних инструментов для разработчиков.

Экспертные знание конфигурации "1С:ТОИР Управление ремонтами и обслуживанием оборудования" в роли ведущего консультанта (аналитика) или функционального архитектора. Участие в процессах проектирования, тестирования, ПСИ, миграция исторических данных интеграции с основной системой 1С ЕРП УХ, внешними системами.

В Отдел аналитики ищем, да да в Отдел аналитики ищем джуна который умеет читать коды Java. Нам нужен начинающий специалист с сильным логическим мышлением, техническим интересом и высокой обучаемостью.

-Разрабатывать и поддерживать веб-приложения на React 18+ и TypeScript. -Применять стейт-менеджеры Redux и Saga/Thunk для управления состоянием приложения.

-Проектирование и реализация backend-логики платформы. -Разработка и документирование REST API для фронтенда.

Разработка и поддержка сервисов, отвечающих пользователям на запросы в поддержку. Разработка HTTP API с использованием FastAPI, Django и SQLAlchemy.

-Разрабатывать и поддерживать сервисы, отвечающие пользователям на запросы в поддержку. -Разрабатывать HTTP API с использованием FastAPI, Django, SQLAlchemy.

Задачи: - Самостоятельно дорабатывать функционал платформы на Java (21) - Тестировать новый функционал - Анализировать ТЗ и согласовывать планы выполнения работ для текущих задач - Локализовывать дефекты, расследовать инциденты и повышать качество программного продукта Требования: - Опыт работы бэкенд-разработчиком от 3 лет, опыт коммерческой разработки - Опыт работы с системами управления версиями Git - Опыт разработки решений в монолитной и микросервисных архитектурах - Опыт работы с реляционными БД и SQL - Опыт работы с REST/API и Kafka, опыт работы с OAuth - Базовые знания и опыт работы с CI/CD на уровне понимания и небольшой донастройки пайплайнов - Желательно: базовые навыки работы в Linux, умение работать с системами логирования и мониторинга, Distributed tracing, опыт работы с GitLab Условия: - Официальное оформление со всеми социальными гарантиями - Формат работы: удалённо или гибрид

- искать технические решения для проектных задач. - прорабатывать проект поэтапно: сначала эскизы и концепция, потом план — какие риски, что проверить, как протестировать.