Вакансии

Роль включает тестирование, координацию подгруппы, наставничество и участие в приёмочных испытаниях. Требования: Базовые знания в области тестирования и от 3 лет опыта функционального тестирования веб-приложений и проверки документации.

- Разработка и улучшение пайплайна LLM post-training: SFT, preference optimization, Offline / Online RL; - Улучшение instruction following и построение системы benchmarking / evaluation;

Задачи: — Подготовка тест-кейсов на основании требований и критериев приемки инициатив — Функциональное и интеграционное тестирование ИИ-агентов, workflow на платформе Dify, API-интеграций со внутренними системами — Проверка позитивных, негативных и пограничных сценариев, включая нетипичные запросы пользователей и «галлюцинации» модели — Регрессионное тестирование после изменений промптов, моделей, базы знаний (RAG) и интеграций — Проверка соответствия результата согласованным требованиям и метрикам качества — Формирование и поддержание тестовых выборок (golden set) совместно с бизнесом и ML-командой, участие в оценке качества ответов — Фиксация дефектов, контроль их устранения, отчётность по качеству релизов — Проведение приемочного тестирования перед выпуском в production и участие в приемке с бизнесом Требования: — Опыт работы от 3 лет в тестировании ПО — От 1 года тестирования продуктов на основе ML/LLM или тестирования API и интеграций backend-сервисов — Понимание специфики недетерминированных ответов модели — Не менее 2 проектов тестирования интеграционных / API-решений или ИИ-продуктов с выводом в промышленную эксплуатацию — Опыт построения регрессионных наборов и тестовых выборок — Желательно: опыт в e-commerce, ритейл, B2B-дистрибуция, клиентский сервис — Тест-дизайн, тестовая документация, работа с баг-трекером — Тестирование REST API (Postman или аналоги), чтение JSON, логов — SQL на уровне выборок для проверки данных — Python на базовом уровне для скриптов проверки и подготовки тестовых данных — Понимание принципов работы LLM, RAG, промптов и метрик качества ИИ (точность, полнота, оценка ответов по критериям) — Желательно: опыт работы с платформами оркестрации LLM (Dify, LangChain и т.п.) — Желательно: автоматизация тестирования API (pytest, requests) и LLM-eval инструменты (RAGAS, DeepEval, promptfoo или аналоги) — Желательно: опыт разметки и оценки ответов модели (LLM-as-a-judge, ручная оценка по рубрикам) — Желательно: CI/CD, Git на базовом уровне — Системы учета задач и документации: Jira / Yandex Tracker, Confluence / Yandex Wiki, Git, реестр ИИ-инициатив в Google Sheets Условия: — Занятость: фултайм — Формат работы: удалённая по РФ или в офисе в Москве/Саранске (hybrid) — Тип контракта: ГПХ, ИП — Оплата до 1400 руб./час гросс

Location: Москва Мы - направление Сбербанк Онлайн и AI-помощник в дивизионе Премиальный сегмент. Наша общая цель – развивать интеллектуальные сервисы для повышения качества обслуживания премиальных клиентов и эффективности работы сотрудников. Одно из ключевых направлений – комплексный AI-анализ коммуникаций менеджеров с клиентами: анализ транскрибированных диалогов и аудиосигнала, контроль стандартов обслуживания, выявление эскалаций и пропущенных элементов, анализ тональности и речевых характеристик, а также формирование рекомендаций для сотрудников и руководителей. **Почему мы:** ·      Развиваем прикладные AI-решения, которые быстро проверяются на реальных бизнес-сценариях; ·      Есть возможность работать не только с LLM и prompt-based подходами, но и с классическим ML, NLP, Speech и собственными моделями; ·      Доступна внутренняя инфраструктура для обучения моделей и использования GPU-ресурсов; ·      Можно участвовать в развитии решений на базе GigaChat, RAG, LoRA и агентных подходов; ·      Небольшая AI-команда: заметное влияние на архитектуру, эксперименты и итоговый продукт; ·      Сильное бизнес- и IT-окружение, высокие темпы вывода решений в эксплуатацию. Обязанности ·      разрабатывать и улучшать ML/NLP/LLM-компоненты для анализа коммуникаций менеджеров с клиентами ·      работать с текстом и аудио: исследовать тональность, речевые паттерны, паузы, темп и другие доступные признаки коммуникации ·      решать задачи классификации, скоринга и извлечения признаков из диалогов: эскалации, тематики, соблюдение стандартов, обязательства перед клиентом и другие бизнес-сигналы ·      разрабатывать и сравнивать baseline-подходы: правила, prompt-based LLM, классический ML, нейросетевые модели и их комбинации ·      готовить данные для экспериментов, формировать обучающие и валидационные выборки, проводить error analysis ·      оценивать качество моделей и LLM-компонентов, подбирать метрики и критерии приемки ·      участвовать в fine-tuning/LoRA и обучении собственных моделей там, где это оправдано и доступно во внутреннем контуре ·      участвовать в развитии RAG- и агентных сценариев на базе внутренних AI-решений ·      совместно с Python-разработчиком и аналитиками проектировать AI-pipeline от входных данных до результата, доступного бизнес-системам ·      участвовать в Code Review, технических обсуждениях, документировании решений и выводе AI-компонентов в промышленную эксплуатацию. Требования ·      хорошее знание Python ·      поонимание основ машинного обучения: постановка задачи, подготовка данных, обучение, валидация, переобучение, data leakage и выбор метрик ·     практический опыт с базовым стеком web-frameworks python и/или другими современными инструментами ·      понимание принципов работы LLM, prompt engineering, RAG и подходов к оценке качества генеративных моделей ·      умение проводить воспроизводимые эксперименты и аргументированно сравнивать несколько подходов к одной задаче ·      знание NumPy, pandas и scikit-learn либо сопоставимых инструментов **Будет плюсом:** ·      опыт Speech/Audio ML: acoustic features или анализ эмоций по аудио ·      опыт в NLP: классификация текстов, embeddings, transformers, извлечение признаков или близкие задачи ·      опыт fine-tuning LLM, LoRA, работы с embeddings и векторным поиском ·      опыт с CatBoost/LightGBM и predictive ML-задачами ·      опыт разработки или эксплуатации ML-сервисов, контейнеризации и оркестрации ·      опыт работы в крупных корпоративных контурах с повышенными требованиями к безопасности. Условия ·      гибкий график начала рабочего дня ·      уровень заработной платы определяем по итогам собеседования, отталкиваемся от ваших ожиданий ·      команда профессионалов своего дела ·      возможность развития по направлениям ·      ДМС с 1-го дня работы ·      обучение и сертификация за счет компании (в том числе обучение английскому языку компенсируется) ·      скидки от партнеров и корпоративные программы ·      рыночная заработная плата и годовая премия по итогам ·      выстроенные процессы по адаптации, оценке и понятную систему роста в компании; ·      наставник на период адаптации и корпоративную жизнь, в которой можно участвовать по желанию ·      сплоченная команда, agile-практики и помощь в профессиональном развитии.

Location: Toronto, Ontario Workplace: Hybrid Artificial Intelligence. Actual Impact. At Docebo, we’re using AI to change how people learn at work—and we mean actually change it. We’re an AI-powered learning platform that helps organizations create, deliver, and manage training all in one place. But our real mission goes deeper: we help teams move faster, work smarter, and focus on the work that truly matters. Our platform is built with intelligent, time-saving tools that personalize learning, eliminate busywork, and turn training from a checkbox into a superpower. The result? Better experiences for learners and real results for businesses. We’re shaping the future of learning with a team that isn’t afraid to challenge the status quo. If you're excited by the idea of using AI to make work-life better for real people–you’ll feel right at home here. And it’s not just what we build, it’s how we show up. At Docebo, our values aren’t just posters on the wall—they guide how we work every day. We call it the Docebo Heart: trust by default, assume positive intent, and create space for different perspectives to thrive. So… what are you waiting for? Join 900+ Docebians around the world and help us reinvent the way people learn, because learning never stops. THE ADVENTURE AHEAD 🚀 As a Senior Product Engineer II, you bring deep expertise in backend engineering alongside strong working competency across the broader stack. You own complex features and technical initiatives end to end, working across services, APIs, data layers, and integration boundaries to deliver complete solutions. Your primary strength is building reliable backend systems, designing scalable APIs, and shaping cloud native and event driven architectures. You understand how the broader system fits together and can confidently work across frontend and platform boundaries when needed. Beyond your individual technical output, you function as a technical anchor within your squad. You help drive technical direction, mentor peers, coordinate dependencies, and ensure the team can consistently deliver high quality software without creating unnecessary knowledge silos.   THE DAY-TO-DAY ⚒️ - Own complex initiatives end to end Drive multi sprint technical initiatives from architecture through implementation, production deployment, and ongoing evolution. - Build reliable backend systems Design and evolve services, APIs, data models, and asynchronous workflows that support complete customer outcomes. - Work across system boundaries Navigate frontend applications, backend services, data layers, and platform integrations to deliver complete solutions. - Set technical direction Bring deep backend expertise while shaping architecture decisions and engineering patterns across the broader system. - Make durable technical decisions Evaluate complex tradeoffs around consistency, performance, reliability, and security, balancing immediate delivery with long term scalability and maintainability. - Anchor the squad Break down complex work, coordinate technical dependencies, unblock others, and help the team maintain delivery momentum. - Drive engineering excellence Raise the bar for testing, CI/CD, observability, architecture, code quality, and pragmatic technical debt management. - Partner across functions Work with Product, Design, QA, SRE, platform teams, and engineering groups to translate customer problems into reliable solutions. - Level up the team Mentor engineers through architecture discussions, design reviews, code reviews, pairing, and knowledge sharing. YOUR SUPERPOWERS⚡️ - Engineering depth and breadth Six or more years of software engineering experience, with deep expertise in backend engineering and strong working competency across the broader stack. - End to end ownership A proven record of owning complex technical initiatives from architecture through production deployment and operation. - System design expertise Strong understanding of service architecture, APIs, distributed systems, cloud services, and maintainable production software. - Data modelling and databases Strong experience designing and evolving data models, schemas, and access patterns, with an understanding of relational databases, query performance, indexing, migrations, and data integrity. - Asynchronous and event driven systems Experience building reliable background processing, messaging, and event driven workflows across services and integration boundaries. - Production reliability The ability to reason about failure modes, concurrency, retries, data consistency, and performance across services and integration boundaries. - Technical leadership The ability to guide engineers through uncertainty, establish effective architecture patterns, and raise engineering standards. - Integration fluency Comfort navigating unfamiliar systems and safely evolving APIs, service contracts, and integrations, including the frontend applications that depend on them. - Engineering excellence Strong experience with automated testing, CI/CD, observability, monitoring, and pragmatic technical debt management. - Collaborative communication The ability to explain tradeoffs, challenge assumptions constructively, and align Engineering, Product, Design, QA, and platform stakeholders. BONUS POINTS 🌟 - Cloud and event driven systems Cloud native applications using serverless services, messaging, asynchronous workflows, or event driven architecture. - Infrastructure and delivery Infrastructure as Code, CI/CD pipelines, deployment strategies, or production operations. - Backend breadth Experience across multiple backend languages, frameworks, or runtime environments, and confidence choosing appropriate tools for the problem. - Security and tenancy Authentication, authorization, tenant isolation, and secure handling of customer data. - Frontend competency Working experience with modern frontend frameworks, application state, and API integration. - Production observability Monitoring, tracing, logging, metrics, incident diagnosis, and performance tuning. - Technical growth Experience acting as a technical lead or clear progression toward broader Staff level leadership. OUR STACK 🛠️ - Backend and platform systems include Node.js, Go, PHP, Python, AWS, REST APIs, event driven architectures, relational databases, CI/CD, and modern observability tooling. Frontend applications include Angular and modern web technologies. - You do not need deep expertise in every technology we use. We are looking for deep backend expertise, strong software engineering fundamentals, and confidence applying your experience across languages, frameworks, and system boundaries. OUR HYBRID WORK PHILOSOPHY 🤝 Great work can happen anywhere but coming together helps us go further. Our team spends three days a week in the office (Tuesday-Thursday) to collaborate, solve problems, and learn from each other. With flexibility the rest of the week, it’s a balance designed to help everyone do their best work and keep growing. OUR TOTAL REWARDS PHILOSOPHY 🎉 Our Total Rewards Philosophy centers around three core areas to reward and care for our People: - Rewarding Impact: We lead with competitive pay to reward the impact, skills and traits that fuel our success. - Fostering Holistic Wellbeing: We care deeply about and invest in the whole person with programs that support our people’s physical, mental, and financial well-being. - Empowering Our Talent Culture: We build a culture of trust and empowerment by designing our rewards and benefits with transparency, equity, and flexibility, enabling our people to do their best work and stay for the long haul. OUR PROMISE TO YOU 😍 - Financial Wellness: Own a piece of Docebo through our Employee Share Purchase Plan (ESPP) at a 15% discount, plus a competitive compensation package. - Your Well-Being, Covered: You’ll get access to health benefits, so you can get the care you need when you need it. - Rest, Relax, Repeat: Rest and recharge with paid vacation days, two company-wide Docebo Days, floating holidays for cultural celebrations, and your birthday off! - Family First: We provide coverage offering you time with your little one(s) so you can soak up all those precious moments. Fun fact: we had 30 Docebian babies join the family in 2025! - Connections That Count: Connect with global communities through our Employee Resource Groups (including PRIDE, DWA, BIDOC, and Green Ambassadors) and company-wide events that keep the fun rolling all year long. ABOUT DOCEBO 💙 At Docebo, we create seamless, AI-powered learning experiences for over 3,000 customers worldwide. We have successfully achieved two IPOs (TSX: DCBO & NASDAQ: DCBO https://www.docebo.inc/home/default.aspx), been recognized as a top SaaS e-learning solution, and are growing exponentially in the process. We're a global company, with office across North America, EMEA, APAC, and beyond. Our team is guided by five core values—Grow Together Win Together, Build with Our Customer, Clear is Kind, Own Outcomes, Progress Over Perfection—that shape everything we do. If this resonates with you, now is the perfect time to join one of the fastest-growing learning technology companies in the world. Docebo is an Equal Employment Opportunity employer https://www.eeoc.gov/sites/default/files/2022-10/EEOC_KnowYourRights_screen_reader_10_20.pdf. We are committed to diversity and inclusion in our workforce. All qualified applicants and employees will receive consideration for employment regardless of their race, colour, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, citizenship status, age, disability, genetic information, or any other category protected under applicable law. As a federal contractor, Docebo is committed to the principles of affirmative action and equal employment opportunity for protected veterans and individuals with disabilities. Docebo does not discriminate because of protected veteran status or on the basis of disability, and Docebo takes affirmative action to employ and advance in employment qualified protected veterans and individuals with disabilities. Any individuals requiring a reasonable accommodation or would like to voluntarily disclose a disability or protected veteran status to assist with their employment application should send an e-mail to their recruiter directly.

Задачи: — Проектирование и настройка моделей данных, правил расчёта и пользовательских интерфейсов — Обеспечение корректного взаимодействия платформы с SQL- и Python-компонентами — Совместная с бизнес-пользователями валидация и проверка выполнимости и корректности планов поставок Требования: — Опыт работы функциональным аналитиком/экспертом в задачах Supply Chain Planning — Практический опыт работы с low-code платформами — Понимание принципов работы с SQL — Базовое понимание Python для взаимодействия с технической командой Будет плюсом: — Опыт работы с платформой In.Plan Условия: — 164 часа на проект в месяц — Длительность: 3 мес (возможна пролонгация) — Занятость: Full time — Локация: только РФ — Выход: ASAP

Location: Boston, MA; Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY; Washington, DC About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Endpoint team (Client Platform Engineering) treats Anthropic's device fleet as a platform we build and run. We run our own MDM as a production service and manage every piece of device configuration as code. Policies, configuration profiles, queries, remediation scripts, and software all ship through pull requests, CI, a staging environment, and a canary group before they reach the fleet. The fleet is mostly macOS, plus a small number of Linux machines and a growing mobile footprint. You'll own that platform end to end: the infrastructure underneath the MDM, the configuration on top of it, the patching and software pipelines that keep thousands of devices patched and secure, and the telemetry that tells us what is actually true on every device. You'll also build automation that cuts down on manual operational work. You'll work with Security teams on hardening, compliance controls, and detection and response, and with developer and infrastructure teams to make sure those controls don't get in the way of their work. Your work will let us base access decisions on whether a device can be trusted. We value people who double check a compliance report before they believe it. The team is deliberately lean and runs with high autonomy. You'll help define the endpoint roadmap, make architecture decisions, and own the platform every Anthropic employee's work runs on. You'll also help us meet the security standards our Responsible Scaling Policy requires as models advance. Responsibilities Own endpoint configuration as code: author, review, test, and progressively roll out MDM policies, configuration profiles, and remediation scripts across macOS and mobile, with canary stages and rollback built in Operate the MDM platform itself as a production service, including infrastructure as code, observability, upgrades, and incident response Build patch management automation with rapid enforcement timelines while maintaining good user experience Design zero touch provisioning that turns a sealed box into a productive machine on day one Support a small number of Linux machines alongside the Mac fleet Turn fleet telemetry into policy, dashboards, and early drift warnings, and use Claude to automate manual ops work Partner with Corporate Security on endpoint hardening, binary authorization, and compliance controls Take shifts on the team's rotation for incoming requests and escalations, and serve as the deep escalation tier for endpoint issues IT Operations can't resolve You may be a good fit if you Have 8+ years building secure IT systems in complex environments, including leading projects across multiple teams Have managed endpoint fleets of thousands of macOS devices through a modern MDM Treat endpoint configuration as code that is version controlled and peer reviewed, rather than clicking in consoles Go deep on macOS internals such as launchd, configuration profiles, TCC, and system extensions Write Python and shell scripts Write design docs and runbooks so teammates can review and support what you build Strong candidates may also have Have operated an MDM or device management platform as a service, not only consumed one as SaaS Have worked with open source endpoint and device management tooling (Munki, osquery, AutoPkg) Have built automated, progressive rollout systems with promotion gated on telemetry Have experience running infrastructure as code in a public cloud Have working knowledge of Linux administration (packaging, systems, config management) Have used LLMs to automate ops work Deadline to apply: None. Applications will be received on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $285,000 — $325,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Key requirements: experience with at least one modern language such as Java, Python, C++, or C#.

• Design and develop human-like, action-level chatbots that not only converse naturally but also initiate and execute user workflows inside the product. • Participate in the architecture and development of an intelligent, context-aware translation system that preserves meaning, tone, and style.

Location: United Kingdom; Poland; Portugal; France; Spain; Germany; Italy Recognised on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads. The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla. We’re on a mission to transform how companies use data. Come be a part of our journey! ABOUT THE TEAM The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them — together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists.   WHAT YOU WILL DO - Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform. - API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services. - Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools. - Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation. - Oncall: Participate in the daytime oncall rotation along with the rest of the team. - ML Engineering: Own the ML pipeline end to end (data, training, evaluation), and fine-tune or train custom models when off-the-shelf ones fall short. Track the state of the art closely enough to apply what genuinely improves our products. WHAT YOU WILL BRING ALONG - 5+ years of software engineering experience in production environments - Exposure to working directly with AI/ML technologies - Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases - A high level of ownership and can drive features from concept to production with minimal supervision - Ability to thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders - Applied ML experience in Python (Jupyter, PyTorch, common ML libraries), hands-on with compute clusters (Ray, Slurm), and designs trustworthy experiments to drive architectural decisions Nice to have - Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment - Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus - Experience with embedding-based systems (retrieval, ranking, recommenders) and the representation-learning ideas underneath them 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.

Задачи: — Разработка бэкенда на Python — Работа с Prompt Engineering и Agentic AI (LangChain) — Разработка Agent Skills и Tools — Работа с SQL и Snowflake — Работа с Cortex Analyst, Text-to-SQL / Intent-to-SQL Требования: — Английский B2+ — Опыт разработки бэкенда на Python — Опыт Prompt Engineering — Опыт с Agentic AI, предпочтительно LangChain — Опыт с Agent Skills и Tools — Опыт работы с SQL — Опыт работы со Snowflake — Опыт работы с Cortex Analyst — Опыт работы с Text-to-SQL / Intent-to-SQL — Опыт с DeepEval (желательно) — Опыт с MLflow instrumentation (желательно) — Опыт тюнинга стоимости и производительности (желательно) — Опыт с metrics cache и pre-aggregation (желательно) — Опыт в DataOps / Data Platform (желательно) — Понимание архитектуры semantic-layer (желательно) — Опыт в Pharma Commercial (желательно) Условия: — full-time — Долгосрочное сотрудничество

Ищем Senior QA в Desktop-команду — человека, который будет отвечать за качество продукта, развивать автоматизацию и помогать команде внедрять AI в процессы тестирования. Чем предстоит заниматься:

React + TypeScript, Python (FastAPI), PostgreSQL, Docker, GitLab CI. • человека с опытом в стартапе или небольшой команде;

Задачи: — Проектирование и реализация backend- и frontend-частей веб-приложений и внутренних систем — Разработка async API и сервисов на Python (Litestar, FastAPI) — Проектирование моделей данных, схем БД и миграций — Работа с аналитическими нагрузками: тяжёлые запросы, агрегации, оптимизация под OLAP — Проработка бизнес-логики и доменных моделей (DDD), слоистая архитектура — Интеграция сервисов между собой: gRPC, брокеры сообщений, фоновые задачи — Контейнеризация сервисов и настройка окружений (Docker, GitLab CI) — Разработка пользовательских интерфейсов на React + TypeScript — Интеграция фронтенда с backend-API, кодогенерация клиента из OpenAPI, обработка edge-кейсов — Разработка и поддержка переиспользуемых UI-компонентов — Участие в проектировании архитектуры приложений и выкатка своего кода в прод Требования: — Опыт коммерческой разработки от 3 лет, из них год+ в роли fullstack — Python 3.12+, полная типизация — Litestar или FastAPI, Pydantic v2, Dishka — SQLAlchemy 2.0, Alembic, asyncpg — PostgreSQL: индексы, план запроса, оконные функции, оптимизация тяжёлых запросов — Опыт хотя бы с одним аналитическим или поисковым хранилищем: ClickHouse, Elasticsearch, Neo4j — Слоистая архитектура, DDD — Git, Docker, GitLab CI (или аналог) — Фоновые задачи и очереди: taskiq или Celery, NATS, Redis — React 19, TypeScript, Vite, bun — TanStack Router, TanStack Query, TanStack Table, Zustand, react-hook-form, zod — Компонентные библиотеки: Mantine 8 либо Tailwind 4 + Radix/shadcn — Feature-Sliced Design или другая явная слоистая структура фронтенда — HTML, CSS, component-based подход — Системное мышление, внимание к качеству кода, самостоятельность в проработке задачи Будет плюсом: — structlog, uv, ruff, pytest с async-тестами — gRPC (grpclib, betterproto2) — MinIO / S3 — Интеграция self-hosted LLM через OpenAI-совместимый API, pydantic-ai — Ansible, Terraform, Grafana — Biome, кодогенерация API-клиента (@hey-api/openapi-ts) — motion, ECharts / Recharts, графовые визуализации — vitest, Playwright Условия: — Полная занятость, работа в офисе — Влияние на архитектуру backend- и frontend-частей продукта — Собственная инфраструктура on-premise, современный стек без легаси — Конкурентная заработная плата, обсуждается по итогам собеседования

Location: London, England Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Global Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. We're looking for a Senior Machine Learning Engineer to join our London office as part of a Global DoorDash Engineering team (working hybrid, 3 days in the office). This role sits in our Consumer Org, where you'll work on recommendation problems with direct, measurable impact on how customers discover relevant content. You’ll collaborate with experienced scientists and engineers across DoorDash, Deliveroo and Wolt, learning from multiple recommendation systems while helping shape the next generation of the experience. What You'll Be Doing Design, develop and improve recommendation, ranking and retrieval models that surface relevant restaurants, dishes, items and content to customers. Own applied ML problems end to end: frame the problem, analyze data, develop models, define offline evaluation, run experiments and monitor production performance. Develop methods that balance relevance with product and customer needs, such as diversity, availability, business constraints and changing user intent. Collaborate closely with Software Engineers, ML Engineers, Product Managers and Analysts to turn scientific insights into reliable customer-facing products. Evaluate and apply state-of-the-art ML methods where they meaningfully improve recommendation quality, robustness or efficiency. Contribute to a high bar for applied-science practice through technical reviews, knowledge sharing and thoughtful experimentation. What You'll Need to Thrive You have substantial hands-on experience applying machine learning to real-world problems and a track record of bringing models from development into production; a PhD with relevant applied research experience is equally welcome. You have experience with recommendation systems, ranking, retrieval, personalisation, or closely related ML problems. You can independently turn an ambiguous customer or product problem into a well-scoped ML approach, make sound trade-offs and drive it to a measurable outcome. You are proficient in Python and experienced with modern ML frameworks and large-scale data processing. You understand how to evaluate ML systems rigorously, including offline metrics, experiment design and interpreting online results. You communicate complex technical ideas clearly and work effectively with cross-functional partners. Why Join Us? At Deliveroo, you'll do work that matters—solving real-world problems in a three-sided marketplace that's constantly evolving. We're food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠 Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎 A culture built for builders High standards, collaboration, flexible working and continuous learning. 💰 Share in the success you help create Competitive salary and equity options, so you're rewarded for the impact you make. ➡️ Want a deeper look at how we build? Check out our Tech Blog. Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness .

Location: New York; Detroit; Canada; Austin; Phoenix; Los Angeles; San Francisco; Dallas Workplace: Remote Recognized on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads. The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla. We’re on a mission to transform how companies use data. Come be a part of our journey! ABOUT THE TEAM The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them — together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists. WHAT YOU WILL DO - Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform. - API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services. - Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools. - Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation. - Oncall: Participate in the daytime oncall rotation along with the rest of the team. - ML Engineering: Own the ML pipeline end to end (data, training, evaluation), and fine-tune or train custom models when off-the-shelf ones fall short. Track the state of the art closely enough to apply what genuinely improves our products. WHAT YOU WILL BRING ALONG - 5+ years of software engineering experience in production environments - Exposure to working directly with AI/ML technologies - Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases - A high level of ownership and can drive features from concept to production with minimal supervision - Ability to thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders - Applied ML experience in Python (Jupyter, PyTorch, common ML libraries), hands-on with compute clusters (Ray, Slurm), and designs trustworthy experiments to drive architectural decisions Nice to have - Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment - Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus - Experience with embedding-based systems (retrieval, ranking, recommenders) and the representation-learning ideas underneath them 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: Germany, Berlin Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Role Overview: We are looking for a Staff Software Engineer to help shape and build the next generation of our network automation platforms. Our challenge is one of scale, complexity and criticality. We operate a massive global network supporting PlayStation Network, spanning more than 40 interconnection locations and 20+ data centres worldwide. Operating infrastructure at this scale safely and efficiently requires us to move beyond specialist-driven workflows and individual automation tools toward reliable, declarative software platforms. You will help make that transition. You will work on software that turns complex network and infrastructure operations into reliable, API-driven and increasingly self-service capabilities. This includes building control-plane services, declarative APIs and intent-based controllers that manage production infrastructure safely and consistently across our global footprint. This is a Staff-level engineering role with significant technical influence. You will combine hands-on engineering with setting technical direction: defining architectures, solving complex cross-system and distributed-systems problems, writing designs, driving alignment with senior engineers and architects, and mentoring engineers across the team. Your work will directly influence how one of the world's largest gaming networks is operated and automated, while establishing engineering patterns and platforms that can be reused across multiple network domains and services. What you'll be doing: Provide technical leadership and architectural direction for network automation and infrastructure control platforms, treating the self-service network API as a product by working with users and partner teams to define outcomes, establish clear expectations for API behavior and reliability, align on team responsibilities, and ensure those commitments are met. Use domain-driven design with network experts, software engineers and API consumers to establish shared language and bounded contexts, then turn those agreements into versioned, testable contracts. Design and build APIs, services, controllers and reconciliation workflows that manage production infrastructure safely at scale. Build on the Kubernetes API, including custom resources and control loops that continuously converge actual state toward declared intent. Own the operational Kubernetes path: CRD rollout, RBAC and admission, controller health, Helm packaging, deployment drift and incident diagnosis. Design distributed workflows that operate correctly under eventual consistency, at-least-once delivery, concurrent writes and partial failure, with idempotency and safe recovery as fundamental properties. Design stable APIs, schemas and data models used across team boundaries, including versioning and backwards compatibility. Develop patterns for multi-tenant infrastructure platforms, including tenant isolation, authorization, policy enforcement and safe automation boundaries. Establish strong approaches to testing, observability and change safety for software that changes live infrastructure. Improve software delivery practices through automated CI gates, versioned artifacts, controlled promotion, and safe deployment and recovery strategies. Lead complex migrations and modernization of existing automation, services and data models, evaluating when components should be evolved, replaced or rewritten, and ensuring safe coexistence, behavioral compatibility and retirement of legacy paths. Drive technical alignment across software engineering, networking, operations and architecture teams; lead decisions within your area of accountability, contribute constructively to decisions owned by others, and make technology choices based on long-term company and product value. Mentor engineers, lead technical and design reviews, and raise software engineering standards across the wider organization. What we're looking for: Must have Deep expertise in a backend language such as Python, Go, Rust or Java, including asynchronous concurrency, static typing, data modelling and validation, API development, packaging and tooling. Strong experience building Kubernetes controllers or operators, including custom resources and reconciliation/control-loop patterns. Strong experience building event-driven distributed systems, particularly eventual consistency, at-least-once delivery, idempotency, optimistic concurrency and partial-failure handling. Experience designing and building self-service, multi-tenant platforms, including tenant isolation, policy and access control. Strong API and schema design skills, including versioning and schema evolution for interfaces consumed by other teams and systems. Demonstrated technical leadership across team boundaries, including driving architectural designs, building agreement among senior technical stakeholders and mentoring other engineers. A track record of taking ambiguous, technically complex problems from architecture through to reliable production systems that manage large-scale infrastructure, such as networks, compute or cloud resources. Nice to have Networking fundamentals, particularly BGP, IP fabrics and VXLAN/EVPN/L3VPN. Working knowledge of Go, sufficient to understand and contribute to adjacent services and controllers. Experience designing testing and observability strategies for production infrastructure automation, including systems and backends that cannot be fully reproduced in CI. Experience with graph databases, or with source-of-truth systems that model infrastructure and its relationships. The impact You will help establish the architecture and engineering practices behind a new generation of network automation, moving from individual scripts and specialist-driven workflows toward declarative, model-driven and reliable platforms. At Staff level, your impact is expected to extend beyond the code you personally deliver. You will help shape the APIs and designs other teams build on, develop other engineers, and establish technical patterns that can be reused across multiple network domains and services. Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: Москва Мы развиваем «Поток» — единую цифровую среду для командной работы, которая объединяет целеполагание, управление задачами, коллаборацию и автопротокол в одном интерфейсе. В рамках нашего проекта, формируем новый юнит «Аналитика встреч». Мы ищем технологического лидера в формате «играющего тренера»: вы будете вести команду и одновременно самостоятельно писать критичный код. Обязанности ### Обязанности * разработка продукта, который помогает сотрудникам запоминать суть встреч * сбор команды и распределение работы по двум направлениям — персональная аналитика и сводки по совместным проектам и темам для команд * обеспечение удобства и пользы продукта: полного охвата, стабильных отчётов и высокого качества инсайтов, аналитики и рекомендаций * создание сводок, которые помогают командам видеть прогресс совместных проектов и тем вместо ручного пересказа * разработка персональных рекомендаций, которые экономят время и помогают не упустить важное из обсуждений * вывод продукта из прототипа в промышленную эксплуатацию и обеспечение охвата на всех сотрудников банка Требования ### Требования * опыт работы с python, pandas, numpy, pytest, langchain, langgraph от 6 лет * опыт работы с llm, ии-агентами, rag, llm-wiki, графовыми бд * знание nlp, классического ml, матстатистики, алгоритмов, постановки и интерпретации экспериментов * понимание микросервисной архитектуры, обработки больших объёмов данных * опыт проектирования ML-платформ и вывода их в прод * опыт создания AI-агентов и использования их в работе будет преимуществом. ### Будет плюсом * опыт работы с fine-tuning, lora, peft * готовность нести ответственность за продукт и фичу целиком — от идеи до пользы для пользователя, проверка гипотез, отслеживание метрик и доведение решения до результата * готовность разрабатывать полноценные решения и прототипы — от бэкенда и данных до интерфейса, активное использование ai-инструментов разработки для быстрого прототипирования * готовность к глубокому погружению в бизнес-смысл решаемой задачи * навык работы в команде. Условия ### Условия * гибридный формат работы из офиса в г. Москва * годовой бонус и ежегодный пересмотр * ДМС с первого дня + стоматологию и льготное страхование для семьи * корпоративный университет Сбера, внутреннюю образовательную платформу, участие в IT-конференциях * офис на Ленинском проспекте с зонами отдыха и спортзалом * льготную ипотеку в Сбере, корпоративную пенсионную программу, подписку СберПрайм с возможностью совместного использования на трёх близких, скидки от партнеров и сервисов группы компаний.