Вакансии

Задачи: — Ручное функциональное, регрессионное, Smoke и приемочное тестирование Web приложений и Backend — Создание и актуализация тестовой документации: дизайн тест-кейсов, составление чек-листов, оформление баг репортов, накопление базы знаний о продуктах — Тестирование UI/UX — Плотное взаимодействие с командой разработки, участие в планировании — Тестирование требований Требования: — Понимание SDLC и потребностей разработки — Умение тестировать требования к ПО — Опыт исследовательского тестирования — Умение формировать чек-лист, предугадывать поведение системы — Знание основных техник тест-дизайна и умение применять их на практике — Владение инструментами для тестирования API — Навыки работы с консолью Linux/Unix-систем, знание основных консольных утилит и умение ими пользоваться — Понимание клиент-серверной архитектуры — Понимание работы сетевых протоколов — Умение составлять простые SQL запросы (select, delete, update и т.д.)

Location: Germany Workplace: Hybrid WHY INTEGRATIONS ENGINEERING AT LANGFUSE Your work puts Langfuse into developers’ hands. Our SDKs are downloaded 26M+ times per month, and for many developers the first thing they touch is an integration — a few lines of code that connect their favorite framework to Langfuse. When that experience is seamless, they’re wow’ed. When it’s not, we might have lost them. You’ll own that critical first impression across 40+ framework integrations. You’ll live at the frontier of LLM application development. The AI framework ecosystem moves fast — new agent frameworks, orchestration libraries, and model providers emerge every week. You’ll be among the first to instrument them, giving you unmatched exposure to how cutting-edge AI applications are built. The developers you serve are some of the most ambitious software engineers in the world, and working closely with them will make you an expert on LLM engineering yourself. Everything you build is open source and immediately visible. All Langfuse integrations are MIT-licensed. When you ship a new integration or improve an existing one, thousands of developers benefit the same day — and they’ll tell you about it in GitHub issues, on Twitter, and in our community channels.   WHAT YOU’LL DO - Build and maintain framework integrations. Langfuse integrates with 40+ frameworks and model providers: OpenAI SDK, Vercel AI SDK, LangChain, LlamaIndex, Pydantic AI, OpenAI Agents, CrewAI, Amazon Bedrock AgentCore, LiveKit, and many more. You’ll own these integrations end-to-end — from initial implementation to ongoing maintenance as frameworks evolve. When a new framework gains traction, you’ll be among the first to instrument it. - Design new integration patterns for emerging frameworks. When a framework or a new agent orchestrator appears, you’ll evaluate it, design the right instrumentation approach (callback handler, decorator, OTEL auto-instrumentation, or a combination), build the integration, write the docs, and ship it. You’ll develop strong opinions on what makes a great integration experience. - Contribute to the core SDKs. While integrations are your primary focus, your work will surface needs in our Python and TypeScript SDKs. You’ll contribute improvements to the core SDK when your integration work demands it — whether that’s a new hook point, better context propagation, or performance optimizations. - Write documentation and integration guides. At Langfuse, docs are part of our core product. When you ship a new integration, the guide ships with it. You’ll own the integration docs, quickstart tutorials, cookbooks, and migration paths that help developers get started in minutes. - Be a voice in the developer community. You’ll engage with framework communities, respond to integration-related GitHub issues, write blog posts about new integrations, and be present in our Slack/Discord channels. You’ll build relationships with framework maintainers and represent Langfuse in the broader AI developer ecosystem. WHAT WE’RE LOOKING FOR - Passionate about the LLM ecosystem. You’ve built real applications with frameworks like LangChain, Pydantic AI, Vercel AI SDK, LlamaIndex, or similar — or you have a deep willingness to go deep and get your hands dirty with every major framework in the space. You’re excited about this ecosystem, not just familiar with it. - Strong in Python and/or TypeScript. You write clean, reliable code. You don’t need to be a systems-level performance expert, but you care about code quality and understand that integrations run inside other people’s production systems. - Product-minded engineer. You think about the developer who’s going to use your integration at 11pm trying to ship a feature. You obsess over the getting-started experience: how many lines of code does it take? Is the error message helpful? Does the docs example actually work? - Self-directed and motivated. You know how to develop conviction about what to build and how to ship it. You don’t wait for detailed specs — you investigate the framework, talk to users, and propose the right approach. - Excited about open source and developer community. You genuinely enjoy talking to developers about their integration challenges, writing clear documentation, and contributing to open source projects. - Thrives in a small, accountable team. Your output is visible and matters. You’re comfortable owning outcomes, not just tasks. CS or quantitative degree preferred, but not required. We care far more about what you’ve built and your hunger to learn. BONUS POINTS - Experience with OpenTelemetry internals or observability instrumentation - Contributions to popular open source projects, SDKs, or developer tools - Experience building developer tooling, CLIs, or client libraries - Former founder or early startup experience - Active presence in AI/ML developer communities (blog posts, talks, open source)   No candidate checks all boxes. If you feel you are a good fit for this role, please go ahead and apply.   PROJECTS YOU COULD OWN - Build and ship a Langfuse integration for an emerging agent framework (e.g., OpenClaw, new OTEL-based instrumentation) - Design the integration pattern for a new category of AI tools (e.g., voice agents via LiveKit/Pipecat) - Create comprehensive quickstart cookbooks that get developers from zero to traced in under 5 minutes - Work with the OpenTelemetry community to improve GenAI semantic conventions - Maintain and upgrade our most popular integrations (OpenAI, LangChain, Vercel AI SDK) as those frameworks ship breaking changes   PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new team member who joins our company receives stock options. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: Home Based - Americas; Home based - EMEA Canonical is a leading provider of open source software and operating systems to the global enterprise and technology markets. Our platform, Ubuntu, is widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation, and IoT. Our customers include the world's leading public cloud and silicon providers, as well as industry leaders across many sectors. Canonical is a pioneer of global distributed collaboration, with 1,200+ colleagues in 75+ countries and very few office-based roles. Teams meet two to four times yearly in person, in interesting locations around the world, to align on strategy and execution. The company is founder-led, profitable, and growing. We are hiring an Engineering Manager for Distributed Systems Testing to lead a team responsible for the quality engineering platform that enables deployment and validation of distributed systems across Canonical's cloud portfolio. We see quality engineering as a first-class engineering practice. Our Distributed Systems Testing team ensures the performance, correctness, resilience and interoperability of Canonical cloud solutions built with technologies such as Juju, Terraform, OpenStack and Kubernetes. These systems are deployed and tested across diverse environments, from bare-metal to the public cloud. As Engineering Manager, you will combine strong software engineering judgement with people leadership. You will develop engineering talent, establish effective engineering practices, shape technical direction with senior engineers, and ensure the team delivers high-quality testing infrastructure and automation that enables engineering teams across Canonical to ship software with confidence. We believe engineering managers should be outstanding engineers themselves. You should be comfortable reviewing patches, evaluating software design, debugging a distributed system, or discussing test architecture. You will contribute technically where appropriate to set a high standard, while recognizing that your greatest impact comes from shaping the direction, focus, effectiveness, and growth of the whole team. You will work closely with senior engineers and engineering leaders across Canonical to define priorities, improve testing capabilities, and advance how we validate increasingly complex cloud-native and distributed systems. Location: This is a globally remote role, typically leading a team concentrated within a major time zone such as EMEA or the Americas. What you'll do Lead, coach, and develop a high-performing team of software and quality engineers, ranging from graduate to senior level Set clear expectations, strengthen engineering practices, and ensure timely delivery against agreed goals Partner with senior engineers to shape technical strategy, architecture, roadmap, and engineering standards Guide the development of automated testing infrastructure for the reliability, interoperability, and resilience of distributed systems Improve CI pipelines, testing tools, and reporting used to validate Canonical's products and solutions across bare-metal, private and public cloud environments Enable engineering teams across Canonical to adopt effective distributed-systems testing practices and tooling Contribute technical leadership through design and code reviews, debugging, and hands-on engineering where appropriate Represent the team with stakeholders and collaborate across Canonical on quality engineering, infrastructure, and developer experience What we're looking for in you An exceptional academic track record from both high school and university Experience in leading, coaching, and mentoring software engineers Professional software engineering experience with Python or Go Expertise in distributed systems, cloud infrastructure, quality engineering, or a closely related domain Strong knowledge of modern software testing processes, strategies, and automation Experience with Linux (Debian or Ubuntu preferred) Strong technical judgement and the ability to engage meaningfully in code reviews, architecture discussions, and software design Experience working in an agile development environment with the ability to organize a team to deliver high-quality results Professional written and spoken English with excellent communication and presentation skills Great interpersonal skills, curiosity, flexibility, and accountability, demonstrating passion, thoughtfulness, and self-motivation Ability to travel twice a year, for company events up to two weeks each Additional skills we value Experience with any of the following: Cloud technologies such as Kubernetes, OpenStack, Juju, Terraform, AWS, Google Cloud, or Azure Designing testing strategies for distributed or cloud-native systems Building or operating large-scale CI/CD and test infrastructure Applying AI or machine learning to test analysis, failure classification, or engineering workflows Deploying, operating, or debugging distributed systems Leading globally distributed teams What we offer colleagues We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually, and more often for graduates and associates, to ensure we recognize outstanding performance. In addition to base pay, we offer a performance-driven annual bonus. We provide all team members with additional benefits that reflect our values and ideals. We balance our programmes to meet local needs and ensure fairness globally. Distributed work environment with twice-yearly team sprints in person Personal learning and development budget of USD 2,000 per year Annual compensation review Recognition rewards Annual holiday leave Maternity and paternity leave Employee Assistance Programme and wellness support Opportunity to travel to new locations to meet colleagues Priority Pass and travel upgrades for long-haul company events About Canonical Canonical is a pioneering tech firm at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and a leading platform for AI, IoT, and the cloud, we are changing the world of software. We recruit globally and set a very high standard for people joining the company. We expect excellence; to succeed, we need to be the best at what we do. Most colleagues at Canonical have worked from home since our inception in 2004. Working here is a step into the future and will challenge you to think differently, work smarter, learn new skills, and raise your game. Canonical is an equal opportunity employer We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration. Requisition ID: 1361

Location: Boston, Massachusetts; Foster City, California; Marlton, New Jersey; Remote, United States Do you care about keeping developer tools running reliably, enjoy digging into the systems and infrastructure behind them, and know that reliable tools make all the difference for development teams? If you are calm under pressure, enjoy diagnosing complex systems, want to help developers overcome technical hurdles, and thrive on deep problem-solving across diverse tech stacks, this role is for you. About JetBrains We create intelligent software development tools for developers and teams. More than 15 million users, over 300,000 companies, and 88 of the Fortune Global Top 100 rely on our products to solve real, complex problems. Our mission is simple: make development teams more productive and AI adoptable at scale. About TeamCity TeamCity is a highly scalable CI/CD server that integrates across the modern software ecosystem. Because it supports complex server-side setups and SaaS deployments, issues can stem from the product itself or the surrounding infrastructure. What you’ll do As part of our Support Engineering team, you will act as a crucial link between global engineering teams and our internal product developers. You will take ownership of incoming technical issues, pinpoint root causes, and provide working resolutions or clear escalations. You'll work American-timezone hours to give our global community timely, effective support. Day to day, you will: Identify whether an issue stems from the product, infrastructure, or third-party integrations. Provide workarounds, submit bug reports, or escalate issues directly to development. Capture insights and publish solutions following KCS (Knowledge-Centered Service) principles. Share user feedback with internal product teams to shape future tool improvements. What you’ll bring A systematic and structured, but flexible approach to troubleshooting complex software and infrastructure issues. A clear, direct communication style that explains technical details in ways others can understand. Comfort working independently across distributed teams and time zones. Curiosity about how different build systems, VCS providers, and clouds operate together. An inclination to leave documentation and systems better than you found them. What you’ll need Fluency in English, with strong written communication skills. The ability to work aligned with American time zones. Practical experience troubleshooting web servers and applications (such as Tomcat and Java-based environments). A working knowledge of relational databases (such as PostgreSQL, MySQL, or MSSQL). Hands-on experience with version control tools and hosting platforms (such as Git or Perforce, GitHub, GitLab, or Bitbucket). Familiarity with build automation tools (such as Gradle, Maven, or .NET build systems). An understanding of containerized environments or cloud infrastructure (such as Docker, Kubernetes, AWS, or Azure). What success looks like Success in this role means resolving complex support cases efficiently while maintaining clear communication with developers. You build trust by accurately diagnosing underlying infrastructure or application bugs rather than addressing symptoms alone. Over time, your contributions to the knowledge base reduce repeat issues, and your feedback helps product teams make TeamCity more resilient. #LI-DNI This range reflects the employer’s good-faith estimate of the base salary it reasonably expects to pay for the position at the time of posting. Starting pay within the range will be determined based on job-related factors such as skills, qualifications, experience, and work location. The base salary range (per year) for this position in the posted work location(s) is $144,000 — $216,000 USD We are an equal opportunity employer We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation. We process the data provided in your job application in accordance with the Recruitment Privacy Policy.

Задачи: – Поддерживать, масштабировать и повышать безопасность локальных кластеров Kubernetes (на собственном сервере, а не в управляемом облаке) для обеспечения высокой доступности и аварийного восстановления. – Разрабатывать, внедрять и управлять инфраструктурой как кодом (IaC) для локальных сред с использованием Ansible и других инструментов автоматизации. – Создавать, оптимизировать и мониторить конвейеры Azure DevOps для CI/CD контейнеризированных приложений и изменений инфраструктуры. – Поддерживать и расширять компоненты инфраструктуры на базе Azure, интегрированные с локальными рабочими нагрузками. – Внедрять и поддерживать стек средств мониторинга: Prometheus, Grafana, Kafka (для потоковой передачи логов/метрик) и мониторинг баз данных (PostgreSQL, MongoDB). – Упаковывать и развёртывать приложения с использованием Helm, обеспечивающие стандартизированные и воспроизводимые релизы. – Разрабатывать и поддерживать скрипты на Bash и Python для автоматизации, устранения неполадок и создания инструментов. – Взаимодействовать с командами разработчиков, специалистов по безопасности и эксплуатации для обеспечения надежности, соответствия нормативным требованиям и производительности платформы. – Документировать архитектуру, процессы и руководства по эксплуатации для обмена знаниями. Требования: – Более 5 лет практического опыта работы в качестве DevOps-инженера в корпоративных средах. – Подтвержденный опыт развертывания и управления Kubernetes в локальной среде (кроме AKS/EKS/GKE). – Уверенное владение Ansible для управления конфигурациями и автоматизации. – Обширный опыт работы с Azure DevOps для проектирования и сопровождения конвейеров CI/CD. – Уверенный опыт работы с Helm для упаковки приложений в Kubernetes. – Практический опыт работы с Prometheus, Grafana и Kafka для мониторинга и потоковой передачи событий. – Опыт управления и мониторинга баз данных PostgreSQL и MongoDB в производственной среде. – Уверенное владение языками программирования Bash и Python для автоматизации и разработки инструментов. – Уровень владения английским языком: B2 или выше — умение четко общаться с международными командами и заинтересованными сторонами. – Продемонстрированная способность к сотрудничеству в команде и с клиентом.

Agvend — B2B SaaS-платформа для агросектора Северной Америки, с 8-летним опытом на рынке, охватывающая около 30% рынка ag-retail в США и Канаде, команда около 150 человек, из которых около 100 в R&D, полностью удалённая работа с офисами в Канаде, США и на Кипре для желающих. Стек технологий: Python, Django, DRF, Postgres, ClickHouse, AWS на бэкенде. TypeScript и React на фронтенде. Модульный монолит с тремя крупными приложениями и микросервисами-сателлитами. 5 продакшн Kubernetes кластеров, около 150 тенантов, примерно 5 тысяч запросов в минуту. Используются CircleCI, Docker/ECR, Helm, Terraform, blue-green деплой. Задачи: — Полноценная fullstack разработка: фичи от API до UI без разделения на бэкенд и фронтенд. — Владение зоной ответственности: архитектура, code review, ответственность за продакшн. — Работа с реальной нагрузкой: Postgres и ClickHouse, мульти-тенант, миллионы записей. Требования: — Senior уровень, 5+ лет коммерческой fullstack разработки. — Продвинутый опыт одновременно на backend и frontend: Python/Django/DRF и React/TypeScript, не просто бэкендер с фронтом "для галочки" или фронтендер с базовыми знаниями Django. — Уверенные навыки Python и Django/DRF, опыт работы с Postgres под нагрузкой. — React и TypeScript на продуктовом уровне, минимум 2 года. — Самостоятельность, ведение зоны без микроменеджмента, прямая работа с PM. — Русский язык — основной рабочий, английский — рабочий уровень. Будет плюсом: — Опыт с ClickHouse и аналитическими базами данных. — Опыт работы с highload и финтех системами. — Знания Kubernetes, Helm, Terraform, CircleCI на уровне умения чинить пайплайны. — Опыт с очередями и распределёнными системами (Kafka, RabbitMQ), понимание идемпотентности. Условия: — Работа в команде только сеньоров, плоская структура (Engineering Manager + senior IC, без техлидов). — Безлимитные отпуска, мягкий менеджмент, отсутствие фиксированных часов, асинхронная коммуникация. — Оффсайты два раза в год (Кипр, Грузия/Армения). — Бюджет на обучение, конференции, технику. — Очень низкая текучесть, многие работают по 5–6 лет. — Коммуникация внутри команды на русском языке.

Задачи: — Разрабатывать Python / SQL-пайплайны загрузки и обработки данных из файлов, API и информационных систем. — Проектировать таблицы хранилища: сущности, связи, правила преобразования. — Встраивать псевдоанонимизацию и проверки качества в потоки данных. — Готовить признаки и версионируемые train/validation/test-выборки. — Обеспечивать прослеживаемость и воспроизводимость ML / LLM-экспериментов. — Вместе с ML-командой развивать оценку моделей, подготовку данных для RAG и дообучения. Требования: — Уверенные Python и SQL, поддерживаемый код за пределами ноутбуков. — Практический опыт ETL / ELT: оркестрация, инкрементальная обработка, повторные запуски. — Опыт с S3, Parquet, pandas / Polars / PyArrow. — Понимание жизненного цикла ML: выборки, baseline, метрики, проверка утечек. — Опыт с MLflow, ClearML или аналогами. — Linux, Git, Docker, CI/CD. — Умение работать с чувствительными данными. Будет плюсом: — Опыт с медицинскими данными, МИС и клиническими справочниками. — Практический NLP / LLM: извлечение данных из текста, embeddings, RAG. — PyTorch / Hugging Face, дообучение и inference на GPU. — Опыт превращения исследовательского прототипа в регулярный пайплайн. Условия: — Гибридный / удаленный по РФ формат работы. Дополнительно: — Проект в HealthTech, поддержка врачебных решений. — Возможность строить платформу с нуля и влиять на архитектуру. — Работа на стыке Data Engineering, MLOps и LLM с современным стеком.

Location: Москва Мы развиваем направление робототехнических шоу и создаем сценические постановки с участием роботов. В рамках этой задачи мы ищем Motion Control Engineer, который будет отвечать за адаптацию, настройку и развитие алгоритмов управления движением для реальных сценариев эксплуатации. Эта роль предполагает работу на стыке управления движением, машинного обучения, робототехники и практического внедрения на реальных платформах. Основная цель позиции - обеспечивать выразительные, устойчивые и безопасные движения роботов в условиях сценических выступлений, с учетом требований к синхронности, качеству исполнения и надежности. Обязанности * адаптировать существующие двигательные навыки и политики управления под задачи сценических и танцевальных постановок * настраивать параметры движений с учетом особенностей площадки, покрытия, темпа, композиции выступления и количества роботов * разрабатывать и улучшать переходы между движениями и навыками для формирования цельных и устойчивых последовательностей * работать с данными motion capture: анализировать, обрабатывать и использовать их для подготовки новых движений, референсов и обучающих выборок * формировать датасеты для дообучения и адаптации моделей управления. * анализировать качество исполнения движений, выявлять причины нестабильности и определять допустимые условия применения конкретных навыков * разрабатывать, внедрять и дорабатывать алгоритмы управления движением на основе Reinforcement Learning и Imitation Learning * проводить тестирование и валидацию решений как в симуляции, так и на реальном роботе * улучшать модели робота и среды обучения, участвовать в задачах Sim2Real * применять современные подходы из научных публикаций и индустриальной практики * улучшать модель робота и среды обучения, решать задачу Sim2Real. Требования * веренное владение Python * практический опыт работы с PyTorch * опыт разработки или применения алгоритмов Reinforcement Learning и/или Imitation Learning * опыт работы с робототехническими симуляторами, например MuJoCo, Isaac Gym, Isaac Sim или аналогичными * понимание принципов управления движением, стабилизации и построения двигательных навыков * навыки анализа поведения обученных политик и поиска причин нестабильной работы * готовность работать на стыке исследований, инженерной реализации и тестирования на реальной платформе **Будет плюсом:** * опыт работы с данными motion capture * опыт работы с антропоморфными роботами * интерес к сценическому движению, синхронизации и постановке групповых робототехнических номеров. Условия * комфортный современный офис возле МЦК ЗИЛ * ежегодный пересмотр зарплаты и годовую премию * уникальную систему обучения Сбера для профессионального и карьерного развития * расширенный ДМС и льготное страхование для семьи * гибкий дисконт по ипотечному кредиту, равный 1/3 от ключевой ставки ЦБ * подписка "Прайм" с возможностью использования на трех близких * вознаграждение за рекомендацию друзей в команду Сбера.

Задачи: — Разрабатывать и улучшать RAG-приложения: chunking, embeddings, retrieval и reranking. — Создавать LLM-воркфлоу и агентов с использованием LangChain, LangGraph, LlamaIndex, CrewAI или аналогичных. — Разрабатывать переписывание запросов, классификацию намерений, маршрутизацию и структурированное извлечение. — Интегрировать LLM API/модели в производственные системы. — Работать с OpenAI, Gemini, Hugging Face и PyTorch. — Вносить вклад в SFT, LoRA, QLoRA, PEFT и оценку LLM. — Работать с OCR, PDF/DOCX, STT и памятью для диалогов. — Создавать API с Python/FastAPI и работать с Docker, Git, тестированием и CI/CD. — Мониторить и улучшать качество моделей, задержки и стоимость. — Брать ответственность за отдельные функции/компоненты под наставничеством старшего инженера. Требования: — 2–4 года опыта в NLP, ML, информационном поиске или прикладном ИИ. — Сильные навыки Python. — Практический опыт с LLM, RAG и AI-агентами. — Понимание трансформеров, embeddings, prompting, retrieval, chunking и reranking. — Опыт работы с LangChain, LangGraph, LlamaIndex, CrewAI. — Опыт с Qdrant, Pinecone, Milvus, Weaviate, Elasticsearch. — Опыт с OpenAI, Gemini, Hugging Face и знание PyTorch. — Понимание оценки LLM и снижения галлюцинаций. — Навыки работы с FastAPI, REST, Docker, Git. — Знание многоязычного NLP будет плюсом. — Профессиональный английский. Желательно: — Знания SFT, LoRA, QLoRA, PEFT. — Знания BM25, RRF. — Опыт с RAGAS, DeepEval, LangSmith, LangFuse. — Опыт с OCR, STT. — Опыт с Graph RAG. — Опыт с vLLM, TGI, Triton. — Оптимизация под GPU. — Знание корейского языка будет плюсом. Условия: — Возможна поддержка визы и релокации в Южную Корею.

Location: Helsinki, Finland About Wolt At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we’re building the delivery of (almost) everything and you’ll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe. Working at Wolt isn’t always easy, but it’s definitely exciting. Here you’ll learn more, build more, and ship more than in most other companies. You’ll be challenged a lot, but also have a lot of fun on the way. So, if you’re a self-starter with drive and entrepreneurial spirit, this could be the ride of your life. About the Team The Unified Privacy Platform team’s mission is to earn the trust of every DoorDash user by upholding their right to privacy, consent, and transparency. We are building a common privacy foundation across DoorDash, Wolt, and Deliveroo so Consumers, Dashers, and Merchants can understand how their data is used, control their choices, and exercise their privacy rights through simple, consistent experiences. Our work is organized around three connected pillars: the Privacy Center, a unified user-facing destination for privacy controls and rights; the Unified Privacy Platform, which captures and enforces consent, policy, jurisdictional requirements, and privacy actions; and Privacy Operations and Intelligence, which gives Legal, Support, Privacy, and engineering operators the workflows, diagnostics, audit history, and automation needed to resolve privacy work safely and efficiently. Together, these capabilities turn fragmented, one-off compliance work into reusable platform primitives that can support new products, brands, and emerging regulations. About the Role DoorDash is looking for an Engineering Manager to lead the Unified Privacy Platform team. You will lead a team of backend and platform engineers responsible for the next generation of privacy and consent infrastructure, including the Privacy Center, the User Consent Platform, privacy-policy decisioning, self-service data-rights experiences, and the operational tooling required to manage privacy cases at global scale. As the Engineering Manager, you will own and execute a multi-year vision for privacy at DoorDash. You will balance legal and regulatory correctness, user trust, security, reliability, and developer velocity while building systems that work consistently across DoorDash, Wolt, and Deliveroo. You will be a strategic partner to Product, Legal, Security, Data Governance, Marketing and Communications, and engineering leadership, establishing clear ownership boundaries and turning complex privacy requirements into scalable, self-service capabilities. You’re excited about this opportunity because you will… Lead and mentor a high-performing team of backend and platform engineers, fostering a culture of ownership, privacy by design, operational excellence, and thoughtful cross-functional partnership Drive the technical strategy across the Privacy Center, the Unified Privacy Platform, and Privacy Operations and Intelligence Build the cross-brand User Consent Platform, including canonical consent state, policy and configuration management, consent SDKs, audit history, and consistent enforcement across products and jurisdictions Deliver simple, self-service experiences for consent and communication preferences, Right to be Forgotten (RTF), Right to Information (RTI), and Data Subject Access Requests (DSARs) Turn emerging privacy and regulatory requirements into standardized platform capabilities instead of one-off product implementations Lead the migration from fragmented legacy consent systems to a single source of truth across DoorDash, Wolt, and Deliveroo, while managing compatibility and safe deprecation Define clear contracts with data-governance fulfillment systems and downstream product and storage teams so privacy actions are traceable, retryable, auditable, and correctly reflected back to users and operators Provide architectural guidance for distributed systems that manage sensitive user choices, policy evaluation, orchestration, secure data delivery, reporting, and immutable audit trails Partner with recruiting to build a diverse and inclusive team, attracting and retaining exceptional engineering talent We’re excited about you because you have… A bachelor’s, master’s, or doctoral degree in Computer Science or a related field, or equivalent practical experience 3+ years of experience in people management leading backend or platform teams 8+ years of industry experience Extensive experience as an engineer or engineering leader in a fast-paced, platform-focused development environment Proven experience designing large-scale distributed systems, service application programming interfaces (APIs), policy or rules engines, workflow orchestration, state machines, data-lifecycle systems, or audit architectures Preferred experience with privacy, consent, data governance, or regulatory systems, including concepts such as the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), California Privacy Rights Act (CPRA), data-subject rights, retention, deletion, and legal holds The ability to translate ambiguous legal, policy, and product requirements into clear platform boundaries, reusable abstractions, and executable roadmaps Strong product sense and the ability to partner effectively with Legal, Product, Design, Security, Data, Marketing, Support, and engineering teams across multiple brands and geographies A growth mindset—you are eager to expand your skills, raise the quality bar, and build enduring systems in a rapidly changing environment Our Commitment to Diversity and Inclusion We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. Beware of recruitment scams: DoorDash, Deliveroo, and Wolt will never ask you to pay money or share sensitive financial information during hiring — learn more about our legitimate recruiting process at Recruitment Scam Awareness - DoorDash .

About the Role: AI Gateway provides developers a unified API to connect applications and agents to hundreds of AI models, handling provider routing, billing, observability, and security controls. The Design Engineer will own product design and frontend implementation across multiple interfaces including dashboard, public model catalog, CLI, API responses, and code. Responsibilities include working with customers, product managers, and engineers to understand problems, explore solutions, build and ship production experiences, and learn from post-launch results. The role involves designing and building production experiences across website, dashboard, CLI, and APIs, making complex AI-related concepts understandable and creating extensible design patterns. The engineer will ensure quality after launch, including visual and interaction craft, accessibility, performance, resilience, and instrumentation, and will use coding agents to explore and implement ideas. What You Will Do: — Own product design and frontend implementation for the journey from discovering a model to operating AI in production. — Design and build production experiences across website, dashboard, CLI, and APIs. — Make models, providers, credentials, routing, budgets, logs, performance, privacy, and governance understandable and create extensible patterns. — Engage directly with customers and use product data to understand problems, define success, and improve the product. — Maintain quality after launch including accessibility, performance, and resilience. — Use coding agents to explore, test, debug, and take responsibility for shipped code. About You: — Demonstrated experience in identifying, designing, building, shipping, and learning from production-quality web applications. — Proficient in React and TypeScript, able to contribute confidently in a large codebase. — Strong visual and interaction design skills, able to make technical or data-rich products understandable while retaining advanced user control. — Comfortable working across graphical interfaces, CLI workflows, API behavior, and implementation details, with attention to accessibility, performance, failure recovery, and instrumentation. — Use customer research and product data to make decisions, communicate clearly, challenge ideas constructively, and adapt based on evidence. — Experience using coding agents daily, with ability to explain, test, debug, and take responsibility for code produced. — No required path; candidates may come from product design, frontend engineering, creative development, or other backgrounds. Bonus If You: — Have experience with developer tools, infrastructure products, model marketplaces, or observability. — Have worked with AI models, providers, inference platforms, guardrails, or AI application tooling. — Have experience with APIs, command-line tools, structured product content, or agent-facing interfaces. — Have built applications or agents with Vercel’s AI SDK or AI Gateway. Compensation & Benefits: — Competitive compensation package including equity. — Inclusive Healthcare Package. — Mentorship and support for professional growth including events. — Flexible Time Off. — Equipment and WFH budget provided. — Salary range for San Francisco base: $208,000 - $312,000 per year, adjusted by location. Work Format: — Fully remote for candidates located beyond commuting distance from SF, NY, London, or Berlin offices. — In-office anchor days (Monday, Tuesday, Friday) if within commuting distance. Equal Opportunity: — Vercel is committed to an inclusive community and does not discriminate based on protected characteristics. — Encourages all to apply even if not meeting every job description criterion.

Задачи: — Проверка микрофронтов и корректности работы ролевых моделей (разные права доступа у пользователей) — Тестирование интерфейсов (UI/UX) на соответствие требованиям — Проверка контрактов между Frontend и Backend, а также между микросервисами (REST API) — Проверка внутренней бизнес-логики микросервисов — Проверка корректности вычитывания операций из блокчейн-сети — Проверка записей транзакций в блокчейн (контроль целостности и неизменяемости) — Проверка механик оффчейн-сбора консенсуса (критически важный процесс для ЦФА) — Написание и поддержка автотестов на Java (TestNG) — Разработка эмуляторов и заглушек (Wiremock) для изолированного тестирования микросервисов — Настройка и конфигурирование тестовых сред — Работа с инструментами мониторинга для анализа поведения системы под нагрузкой и в штатном режиме — Подготовка тестовой документации и отчетов по качеству продукта Требования: — Высшее техническое образование — Уверенное владение SQL (все базовые команды, JOIN-ы, вложенные запросы, фильтрация данных) — Глубокое понимание REST API (методы, коды ответов, авторизация, работа с JSON/XML) — Опыт разработки автотестов на Java с использованием TestNG — Опыт работы с инструментами мониторинга (Kibana, Grafana, Zabbix или аналоги) — умение читать логи и метрики — Базовое понимание принципов интеграции с блокчейн-сетями (как приложение взаимодействует с распределенным реестром) — Опыт подготовки тестовой документации (тест-кейсы, чек-листы, отчеты о дефектах) — Опыт настройки и конфигурирования тестовых сред (поднятие стендов, обновление конфигов) — Практический опыт разработки эмуляторов/заглушек (Wiremock) Будет плюсом: — Опыт тестирования блокчейн-решений или финансовых платформ — Понимание основ криптографии и управления ключами — Опыт работы с микросервисной архитектурой и Kubernetes/OpenShift — Опыт тестирования асинхронных взаимодействий (Kafka, очереди сообщений) — Знание BDD-подхода (Cucumber, Gherkin)

Location: Brisbane, Australia VALD is the world leader in technology for the allied health industry, providing innovative human-measurement technology to over 10,000 clients in over 100 countries. If you have a favorite team in the NBA, EPL, or NFL, there's a good chance they use VALD Technologies. Years on from its humble beginnings in Brisbane, Australia, VALD has grown to a team of over 300 team members in over 30 countries, with five offices across four continents. Driven by a multidisciplinary team of researchers, clinicians, sports scientists, designers, developers and engineers, VALD’s suite of systems offer unparalleled insight into human movement, performance, injury risk and rehabilitation. About the role VALD is building the world’s largest musculoskeletal database, with over two billion data points and counting. Using this data, we can help practitioners to objectively assess patients’ progress and make more accurate, data-informed treatment decisions. We are looking for someone who has hybrid experience in data engineering and data analysis to help shape the future of the VALD Data Lakehouse. In this role, you will Build agentic capabilities: design and ship production agent workflows, including orchestration, tool calling, MCP servers, skills and context management. Ground AI in data: build retrieval, search and data-querying capabilities across our data platforms, including Snowflake Cortex and Databricks. Own quality in production: design and evolve evaluation, monitor quality, feedback, cost and latency, and make improvements to accuracy and robustness Build in safety and security: implement guardrails that keep responses within agreed scope, and ensure each customer's data and context stay securely isolated. Ship through automation: deploy AI components through version-controlled pipelines, promoted consistently across environments and regions. Integrate across teams: work with data engineering, platform and deployment teams to bring AI capabilities into the VALD product suite. Shape what gets built: influence architecture and product decisions, and proactively find ways to improve robustness. Is this you? This is a hands-on engineering role for builders, not a research or manual testing position. You don't need every tool on this page. We'd rather hear about one difficult AI system you've built to solve a business problem and maintained in operation, rather than a long list of technologies you've used. We're chasing: Strong software engineering skills in modern languages, with the depth to own what you build through deployment and operation. A record of shipping LLM-powered or agentic products through to production. Hands-on experience evaluating AI systems and using the results to drive decisions. Practical experience with retrieval, tool use and agent design. A clear communicator who can explain trade-offs to non-technical stakeholders. Beneficial experience: Azure MCPs AI in health and regulated environments Why VALD? You will be working in a fast-paced, dynamic company that has a culture around the belief that anything is possible with hard work, creativity, dedication, and good timing. We have a range of benefits we offer to our team, such as: The opportunity to work in a company that is redefining allied healthcare. Working with a range of high-performing individuals and teams across a range of disciplines. Working with contemporary tooling on industry first applications. Casual work attire. Chefs that prepare you delicious fresh breakfast and lunch. An on-site barista to make your coffee just as you like it. A team gym, masseuse, and access to physiotherapy and exercise physiology services. Diversity & Inclusion Commitment VALD’s best asset is not our technology but our people and culture. A culture of inclusion and diversity is critical to our business. We know diverse teams perform better. It's not a separate initiative – we aim to embed inclusion and diversity in everything we do. We are committed to fostering an inclusive work environment and embracing diversity, including gender, nationality, disability, age, marital/parental status, ethnicity, gender identity, socioeconomic background and sexual orientation. We welcome applications from people from all backgrounds. Apply now We can't wait to meet you and discuss what a career with VALD could look like for you! Successful applicants will be subject to background checks (including identity and criminal record checks). It will be a condition of employment that the background checks return acceptable results. Salary: Up to $200,000 / year

Задачи: — Организация и развитие QA процессов для платформы управления производством. — Взятие на себя ответственности за качество backend-решений и приложений для планирования производственных линий. Требования: — 5+ лет опыта в QA. — Опыт в роли Team Lead или Senior QA. — Опыт построения и управления QA процессами. — Тестирование backend приложений. — Знание Linux, Docker, облачных провайдеров (AWS/GCP/Azure). — Умение работать с неполными требованиями. — Сильные аналитические навыки. — Практический опыт использования современных AI-инструментов. Будет преимуществом: — Опыт построения QA процессов с нуля. — Наставничество QA инженеров. — Опыт с AI-агентами, SAP/ERP, мобильным тестированием, DevOps, CI/CD. — Опыт работы в стартапах. Условия: — Зарплата: $5,000 в месяц — Удалённая работа

Задачи: — Администрировать и развивать Asterisk / IP-телефонию — Настраивать SIP-транки, endpoints, dialplan и маршрутизацию — Работать с ARI / AMI и интеграциями с backend/CRM — Диагностировать SIP/RTP и проблемы качества связи — Работать с Linux, MariaDB/MySQL, CDR — Настраивать безопасность: Firewall, Fail2Ban, ACL — Поддерживать стабильную работу телефонии и автоматизированного обзвона Требования: — От 2 лет практического опыта с Asterisk — Хорошее знание SIP, VoIP, NAT, RTP, кодеков — Linux + базовый SQL — Опыт с ARI и/или AMI — Умение самостоятельно находить и устранять проблемы — Будут плюсом: Redis, Nginx, Grafana/Prometheus, Heplify Условия: — Формат работы: Remote — График: 5/2, 09:00–18:00 — Занятость: Full-time — Зарплата: $3,000 фикс Рассматриваются кандидаты из Армении, Азербайджана, Грузии, Кыргызстана, Молдовы, Узбекистана, Таджикистана.

IT Solve ищет Senior Full-Stack Engineer / Team Lead с сильным опытом Node.js для работы над международными software-проектами. Задачи: — Разрабатывать и поддерживать production backend-сервисы на Node.js — Проектировать и реализовывать REST / GraphQL API — Разрабатывать микросервисную архитектуру — Работать с TypeScript / JavaScript — Разрабатывать frontend-компоненты и приложения на React — Работать с PostgreSQL / MySQL / MongoDB — Использовать Redis, очереди и внешние API-интеграции — Участвовать в архитектурных решениях — Проводить code review — Поддерживать качество и технические стандарты разработки — Работать с Docker, CI/CD и cloud-инфраструктурой — При необходимости участвовать в техническом лидерстве и менторинге разработчиков Требования: — Коммерческий опыт разработки на Node.js — Уверенное знание JavaScript / TypeScript — Практический опыт разработки production backend-систем — Опыт работы с REST API и/или GraphQL — Опыт работы с SQL и/или NoSQL базами данных — Опыт разработки на React — Понимание backend и frontend архитектуры — Опыт работы с Git и CI/CD — Умение проводить code review — Для Team Lead: опыт технического лидерства, менторинга или управления командой разработки будет плюсом Будет плюсом: — Microservices — Event-driven architecture — Redis Условия: — Формат работы: удалёнка — Занятость: полная — Зарплатная вилка: $4,000–6,000 USD gross/month — Финальная компенсация зависит от опыта и уровня кандидата.

Требования: — Имеете законченное высшее или среднее специальное образование — Настроены пройти обучение и дальнейшую стажировку с целью трудоустройства в штат ASTON — Будет плюсом: базовое понимание теории тестирования — Будет плюсом: знакомство с основами Java Условия: — Полная занятость, стажировка — График: 5/2 — Формат работы: удалённо