Вакансии

Задачи: — Разработка и поддержка автотестов для достижения 100% автоматизированного покрытия. — Составление тест-кейсов, тест-планов, чек-листов и протоколов тестирования релизов. — Анализ требований и функционального покрытия. — Автоматизация функциональных, регрессионных и интеграционных проверок. — Тестирование REST API, анализ, воспроизведение и локализация дефектов. — Проверка автотестов на соответствие тест-кейсам, ревью и доработка кода, в том числе созданного с помощью AI. — Работа с JIRA, Confluence и Bitbucket. Требования: — Высшее техническое образование. — Уверенное знание JavaScript. — Опыт написания автотестов на Jest с использованием Playwright или Selenium. — Опыт тестирования enterprise-решений и REST API. — Опыт составления тест-кейсов. — Знание JSON, XML и XSD. — Умение работать с консолью браузера. — Знание методик тестирования и принципов автоматизации. — Умение анализировать требования, оценивать полноту функционального покрытия, анализировать и локализовать дефекты. Будет плюсом: — Участие в реализации веб-проектов с нуля. — Знание Node.js, Express, Sequelize. — Опыт работы с PostgreSQL и ClickHouse. Условия: — Полная занятость. — Гибридный формат работы в Москве. — Оформление по ТК или вариант ИП. — Зарплата 190–230 тыс. рублей на руки. — Предоставляют технику, ДМС со стоматологией, компенсацию фитнеса, скидки на обучение, кино и Skyeng. — Индексация зарплаты.

Location: Poland; UK; Portugal Workplace: remote 1inch is the DeFi ecosystem building financial freedom for everyone. 1inch products help users and builders trade, hold and track digital assets - with the self-custody, comprehensive security and the intuitive user experience they need to unlock the potential of true crypto ownership. 1inch protocols and APIs provide core infrastructure across the DeFi industry and beyond. So if you're someone who thinks big, moves fast and wants to make an impact right from day one, then get ready to join our industry-changing team. Your mission As Data & Analytics Lead, your mission is to turn complex business and product questions into reliable, actionable answers. You will combine AI, data analytics, data engineering, and deep DeFi expertise to build a more intelligent and scalable approach to decision-making. You will use AI not just to accelerate existing analytics, but to rethink how we explore data, test hypotheses, identify patterns, and make insights accessible across the organization. You will be highly hands-on, with expert-level Dune capabilities and a strong understanding of DEXes, DEX aggregators, on-chain data, liquidity, routing, and market dynamics. What you’ll do Create intuitive ways for teams to explore trusted data using AI, natural language, dashboards, and other analytical interfaces. Build AI-enabled workflows and agents that accelerate analysis, uncover insights, and reduce repetitive analytical work, ensuring AI-generated answers are grounded in trusted data, transparent, and verifiable. Turn complex and ambiguous business and product questions into structured analyses, clear insights, and actionable answers. Develop metrics and analytical frameworks that connect user behavior, product performance, on-chain activity, market dynamics, and business outcomes. Proactively identify trends, anomalies, opportunities, and risks, and establish standards for analytical quality, metrics, dashboards, and decision support. Design and evolve data architecture, models, pipelines, and transformations, integrating on-chain and off-chain data into reliable, scalable, and reusable data products. Ensure data is accurate, well-structured, documented, discoverable, and accessible to people and AI systems, with strong standards for quality, observability, maintainability, and performance. Use Dune at an expert level to investigate DEX aggregators, DEXes, swaps, liquidity, routing, users, protocols, and markets, building reusable on-chain datasets and analytical models. Combine blockchain, product, and business data to create a comprehensive view of users, ecosystem activity, and market dynamics, and continuously explore new data sources and analytical approaches. Who you are Deep understanding of DeFi and blockchain data, particularly DEXes and DEX aggregators, including swaps, liquidity, routing, transactions, events, traces, and smart-contract interactions. Expert-level Dune skills, with advanced SQL proficiency and demonstrated experience building sophisticated on-chain queries, datasets, dashboards, and analyses. Strong AI-native way of working, with advanced hands-on experience using Cursor to accelerate analytics and engineering, automate workflows, and build AI-enabled data solutions. Strong proficiency in Python for data analysis, data processing, automation, and AI-enabled workflows. Hands-on experience building and operating modern data platforms with ClickHouse and Airflow, including data modeling, pipelines, transformations, data quality, and observability. Proven ability to turn ambiguous business and product questions into structured hypotheses, robust analyses, and clear, actionable answers. Nice to haves Experience working directly within a DEX, DEX aggregator, DeFi protocol, or other data-intensive Web3 product. Experience working with raw multi-chain blockchain data, including decoding contracts, events, traces, and transactions. Experience applying statistical methods, experimentation, forecasting, or anomaly detection to product and business questions. A strong public track record in the DeFi data ecosystem, such as high-quality Dune dashboards, research, open-source contributions, or community analytics.

Location: Москва Мы — технологическая команда, создающая инновационные решения для спорта. Наш продукт направлен на трансформацию и объективизацию судейства. Мы ищем опытного специалиста в области MLE для участия в разработке и развитии наших решений. **Предстоит** работать с ключевым функциональным и архитектурным ядром нашей системы видеоаналитики, а именно: Обязанности * работать со скелетом как с многомерным временным рядом: сегментация выступления на элементы и фазы, детекция границ (отрыв, приземление, точки экстремума), выделение повторяющихся циклов, temporal action detection на видеопотоке, сглаживание и агрегация предсказаний по времени * участвовать в проектировании API, внутренних контрактов и структуры данных * оптимизировать модели для достижения целевых показателей задержки * развивать высокопроизводительный Python-фреймворк для CV/ML-пайплайна на более чем 15 моделей, работающих единовременно * реализовывать механизмы обработки с multiprocessing и multithreading. Обеспечивать эффективную оркестрацию между CPU и GPU-ресурсами * минимизировать накладные расходы на межпроцессное взаимодействие, копирование данных и работу с памятью. Проводить профилирование и устранять узкие места в video I/O, decode, inference и postprocessing * проводить профилирование и устранять узкие места на всех этапах: Video I/O, декодирование, препроцессинг, инференс, постобработка. Требования * опыт работы ML Engineer / CV Engineer от 3 лет * высокое качество кода на Python (OOP, Pydantic, SQLAlchemy, для DS - NumPy, OpenCV, PyTorch) * опыт реализации сложной вычислительной или бизнес-логики * практический опыт разработки production-ready ML/CV pipeline * опыт работы с видеоаналитикой, обработкой видео или потоковых данных * понимание особенностей Python runtime для высокопроизводительных пайплайнов: GIL, IPC, serialization, shared memory * опыт использования инструментов ускорения инференса: ONNX, TensorRT, TorchScript или аналогов * опыт работы с Linux, Docker, работы в команде в Git, CI/CD Будет плюсом: * опыт разработки расчетных систем * PostgreSQL, ClickHouse, SQLAlchemy * владение компилируемыми языками, такими как Go или C++, для реализации или оптимизации критичных по производительности частей системы * опыт работы со спортивной аналитикой или системами судейства. Условия * комфортный современный офис рядом с м. Кутузовская  * гибридный формат работы * ежегодный пересмотр зарплаты, квартальная и годовая премия * корпоративный спортзал и зоны отдыха более 400 образовательных программ СберУниверситета для профессионального и карьерного развития  * программа адаптации и помощь руководителя на старте  * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа  * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких  * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Москва Команда занимается сбором качественных данных, которые принципиально важны для обучения передовых моделей ИИ. Обязанности * Определять техническую стратегию и целевую архитектуру системы. * Проектировать системы, готовые к масштабированию от миллионов до миллиардов сущностей: горизонтальное масштабирование, шардирование, геораспределение. * Принимать ключевые технологические решения: выбор стека, стратегии хранения, архитектурные паттерны (event-driven, CQRS и др.). * Проектировать end-to-end пайплайны: URL discovery → fetch → parse → deduplicate → store → deliver. * Писать код самых сложных и критичных компонентов: планировщик обхода, URL-фронтир, дедупликация, проводить performance engineering: профилирование, нагрузочное тестирование, устранение bottleneck-ов. * Оптимизировать прокси-инфраструктуру и маршрутизацию трафика на глобальном уровне, исследовать и внедрять новые технологии: HTTP/3, QUIC, eBPF, io\_uring для максимизации throughput, разрабатывать стратегии оптимизации стоимости инфраструктуры (FinOps). * Руководить командой из 3–6 инженеров: планирование, декомпозиция, приоритизация, формировать и поддерживать технические стандарты: Code Review, coding guidelines, архитектурные ADR, менторить разработчиков, проводить 1-1, помогать в профессиональном развитии, взаимодействовать с потребителями данных и смежными командами для планирования roadmap. Требования * **Знание Python и Go.** * Коммерческий опыт разработки на Python и Go от 7 лет, из них не менее 2 лет в роли техлида/тимлида. * Экспертиза в проектировании распределённых высоконагруженных систем (миллионы RPS, петабайты данных). * Глубокое понимание сетевого стека: TCP/UDP, HTTP/1.1/2/3, TLS, DNS, QUIC. * Практический опыт построения масштабных систем краулинга или аналогичных data acquisition систем. * Экспертиза в асинхронном и параллельном программировании. * Опыт проектирования микросервисной и event-driven архитектуры. * Опыт работы с Kafka, Redis, PostgreSQL, ClickHouse (или аналогами). * Уверенное владение Kubernetes, Docker, Terraform, CI/CD. * Опыт работы с облачными платформами. * Навыки глубокого troubleshooting: tcpdump, strace, perf, eBPF-инструменты. * Опыт управления командой: планирование, Code Review, менторинг, 1-1, найм. Будет плюсом ------------ * Знание Rust или C++ для написания высокопроизводительных компонентов. * Опыт работы в компаниях с масштабным краулингом (поисковые системы, data aggregators). * Опыт работы с io\_uring, eBPF, zero-copy networking. * Опыт построения геораспределённых систем. * Опыт применения ML для оптимизации crawl-стратегий (приоритизация, фильтрация, классификация). * Публичные выступления, статьи. Условия * Крупнейшее DS\\&AI community — более 600 DS-специалистов банка. * Дайджест о самых последних разработках в области DS\\&AI и отчеты с крупнейших конференций мира. * Возможность быть соавтором НИРов и статей для международных конференций. * Возможность выбрать удобный формат работы: гибрид или офис. * Ежегодный пересмотр зарплаты, годовая премия. * Корпоративный спортзал и зоны отдыха. * Более 400 образовательных программ СберУниверситета для профессионального и карьерного развития. * Расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа. * Бесплатная подписка СберПрайм, скидки на продукты компаний-партнеров. * Вознаграждение за рекомендацию друзей в команду Сбера.

Location: Austria; France; Germany; Italy; Netherlands; Poland; Spain; United Kingdom Why Kimchi? Great models are raw ingredients. Kimchi is what happens when you ferment them with good engineering. We started inside CAST AI helping companies run LLMs on their own Kubernetes clusters; today we run our own coding harness on any model you pick, and the router deciding which model answers each request is ours too. The Auto Router Our promise is one enforcement layer for your AI: budgets, spend attribution, and model routing, applied before a request ever hits a model. The Auto Router makes the call: for every request, which model serves it. Eight open-source models whose input prices span more than 20×, cached input up to 50× cheaper than fresh, frontier providers on customers' own keys, and a coding agent that fires hundreds of requests before its task is done. Frontier-level task success at a fraction of the token cost: that sentence is the product, and it stays true only if the model inside the router keeps getting better. That model is yours. Made by Cast AI — a Miami-headquartered, globally distributed team across 34 countries that hit unicorn status in January 2026 with a $50B+ backed investment pushing its valuation past $1 billion. About the role Every request gets a decision: which model serves it. This is an applied-ML seat, not an infrastructure one. Platform engineers own the proxy, the streaming path, and the fleet. You own the model inside them: the training data, the objective, the evaluation, and the iteration loop that ships a better router every cycle. The problem: routing is a prediction problem wearing a product's clothes. For every request you predict the quality each candidate model would deliver, what it would cost, and how fast it would decode, and you have to be right enough, in aggregate, that the savings are real and the quality never dips below frontier. The data is messy: rollout outcomes from benchmark harnesses, per-request records from the live fleet, override signals, and token streams whose speed depends on the serving concurrency at the moment. Speed itself is a correctness variable: on deadline-bound agentic work, a model that decodes three times slower doesn't do the same work slower, it does less work. That's why naive cost-per-token objectives quietly optimize for the wrong thing. And the bar for evidence is high: a router change ships only after production-parity evaluation with error bars, then gets held to its numbers in live traffic. Stack: Python; PyTorch; SQL at scale (ClickHouse); OpenAI- and Anthropic-compatible LLM APIs; benchmark and rollout harnesses (RouterBench-class); GitLab CI. Requirements You've spent 5+ years in applied ML or ML research, and you've trained, evaluated, and shipped models that make real-time decisions (ranking, recommendation, bandits, pricing, or LLM routing) and you can tell that story with receipts. Strong Python and SQL at scale: you can pull, clean, and interrogate millions of request-level records without waiting on anyone. You know the difference between a model that got better and an eval that got easier. You have real opinions about what LLM benchmarks measure, agentic harnesses included. You know enough serving reality (TTFT, decode speed, batching, prefix caching, concurrency) to model the objective honestly. You instrument before you optimize, error bars and all. A wide mandate excites you more than it unsettles you. Nice to haves You've worked on LLM routing specifically: RouterBench-class evals, cost/quality/latency Pareto fronts. Calibration, abstention, or conformal methods in production decision systems. You've run online A/B loops with drift monitoring on a model that touches real money. Responsibilities Own the routing model end to end: features, objective, training, calibration, and release cadence. Iterate it like a product, not a research artifact. Build the evaluation that gates every change: production-parity benchmarks, router-vs-router comparisons, holdouts by task family, error bars on pass rates. Nothing ships on vibes. Turn fleet data into training signal: per-request outcomes from production, benchmark rollouts, and override feedback, with failure categorization (infra vs task) so poisoned labels never reach the policy. Model the objective the user actually experiences: task success × token cost × wall-clock speed under the real concurrency regime, with cached-input economics in the picture. Run the online loop: shadow, A/B, full rollout, drift monitoring, retrain. When production disagrees with your offline eval, you find out why before the next ship. Push the frontier where it pays: calibrated decisions, abstention under uncertainty, speed-aware routing. We experiment on what a router should be, not just which model it picks today. Partner with platform engineers on instrumentation: the features and labels recorded per request (decode speed first-class among them) and the experiments the data path must support. What’s in it for you? Competitive salary (depending on the level of experience). Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology Equity options. Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Location: Austria; France; Germany; Italy; Netherlands; Poland; Spain; United Kingdom Why Kimchi? Great models are raw ingredients. Kimchi is what happens when you ferment them with good engineering. We started inside CAST AI helping companies run LLMs on their own Kubernetes clusters; today we run our own coding harness on any model you pick, and we run the models underneath it ourselves. Kimchi Inference One API line and a customer's existing client just works: DeepSeek, GLM, Kimi, MiniMax, Nemotron served serverless from our own GPU fleet (OpenAI- and Anthropic-compatible, pay per token, spend visible per user, team, and key). When control matters, the same models run on the customer's own cluster instead. Behind that one line sits the machinery you'll own: SGLang and vLLM engines, B300 nodes, a shared cluster filesystem that holds every checkpoint exactly once, KV caches riding coding traffic with heavy prefix reuse, and the benchmark harness that gates every change we ship. Made by Cast AI — a Miami-headquartered, globally distributed team across 34 countries that hit unicorn status in January 2026 with a $50B+ backed investment pushing its valuation past $1 billion. About the role Throughput. Latency. Cold starts. Cost per token. Move those four numbers in the right direction and two things happen: customers get faster, cheaper inference, and our margins improve. That's the entire thesis of this role. Every loader you tune, every scheduler decision you land, every kernel you stare at shows up in a customer's p99 and on our P&L. Your mandate is the inference stack's optimization, whatever it takes, and the technical direction of how we optimize it is yours to argue with data. The problem: the checkpoints run 0.3-1.5 TB, and the "right" serving configuration depends on traffic shape, sequence-length distribution, batch dynamics, GPU SKU, memory bandwidth, and quantization tolerance, all variables that shift week to week. Most teams pick a configuration once, over-provision GPUs, and absorb the cost. We don't: we took Kimi-K3 (1.5 TB) from over an hour cold-to-serving to under twelve minutes with a shared filesystem, O_DIRECT weight loaders, and node-local JIT caches, and we're nowhere near done. Prefill/decode disaggregation and tiered KV caches are next. Stack: Python; SGLang; vLLM; TensorRT-LLM; PyTorch; fastsafetensors; CUDA-adjacent tooling; Kubernetes; virtiofs shared filesystems; ClickHouse; OpenTelemetry; Prometheus; Grafana; GitLab CI. Requirements You've built real ML systems for 5+ years, and your portfolio shows depth in inference or training infrastructure, not just model training notebooks. Your Python is production-grade: services, not scripts. You've run vLLM, SGLang, or TensorRT-LLM for real, and you have a working mental model of why an engine performs the way it does on a given GPU. You've measured quantization regressions, not just compression ratios. Multi-GPU and multi-node setups hold no fear: tensor and expert parallelism, collective communication, and their practical failure modes. You know where the bytes live (page caches, O_DIRECT, network filesystems under terabyte-scale reads) and how fast they move. You instrument before you optimize, and you can tell a real win from a benchmark artifact. A wide mandate excites you more than it unsettles you. Nice to haves You've worked on LLM routing specifically: RouterBench-class evals, cost/quality/latency Pareto fronts. Calibration, abstention, or conformal methods in production decision systems. You've run online A/B loops with drift monitoring on a model that touches real money. Responsibilities Push throughput. Continuous batching, chunked prefill, speculative decoding with draft models, CUDA-graph capture, and scheduler tuning across the engine fleet. Find the ceiling on each GPU SKU, then raise it. Cut latency. Attack TTFT and inter-token latency separately; profile to find the actual bottleneck (compute, memory bandwidth, scheduling, storage, or network) and fix it, not the one you assumed. Get more out of the KV cache. Hierarchical and paged attention, prefix caching on heavy-reuse coding traffic, eviction policies, quantized KV. A lot of the unrealized throughput lives here, and you'll own it. Kill cold starts. Weight loaders (O_DIRECT, fastsafetensors-class), JIT and compile caches, shared-filesystem read paths. A 1.5 TB checkpoint has no business taking an hour to reach serving. Quantize without regressing quality. INT8/INT4, FP8/FP4 across weights, activations, and KV, measured on real workloads, not just perplexity benchmarks. Scale across nodes. Distributed inference topologies, network-aware placement, prefill/decode disaggregation, checkpointing strategies that don't bottleneck on storage or interconnect. Set the technical direction. Decide what we benchmark, what we adopt, and what we build ourselves. Bring the team along with strong writeups and reproducible experiments. What’s in it for you? Competitive salary (depending on the level of experience). Enjoy a flexible, remote-first global environment. Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology Equity options. Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks. Spend 10% of your work time on personal projects or self-improvement. Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills. Annual hackathon to spark new ideas and strengthen team bonds. Team-building budget and company events to connect with your colleagues. Equipment budget to ensure you have everything you need. Extra days off to help maintain a healthy work-life balance. Hiring process Screening call with Recruiter Hiring Manager interview Technical interview (system design) Live coding Culture Check interview with an executive As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit. #LI-Remote

Задачи: — Проектирование, разработка и поддержка фреймворка и библиотек для автоматизации тестирования — Разработка инструментов автоматизации установки и настройки продукта под разные среды выполнения — Разработка и автоматизация сценариев тестирования продукта — Интеграция инструментов тестирования в процесс CI/CD (GitLab CI) — Разработка и проведение нагрузочного тестирования продукта Требования: — Обязательное владение стеком: Python (разработка скриптов и утилит), Pytest (написание тестовых сценариев и фикстур), Docker (сборка образов и оркестрация окружений через docker-compose) — Глубокое знание GitLab CI: опыт написания пайплайнов для автоматизации прогонов тестов, настройки артефактов, параллелизации задач и управления динамическими средами — Работа с Git: уверенное владение ветвлением, стратегиями ревью и командной работой в репозиториях — Опыт применения AI-агентов в повседневной работе для ускорения написания кода, генерации тестовых сценариев и анализа логов Будет плюсом: — Опыт с Kubernetes: развертывание тестовых стендов с помощью Helm и работа с кластерами (k3s/minikube) — Опыт написания сценариев на k6 (Go/JS), настройка дашбордов и алертов в Observability Stack (Grafana, Prometheus, Loki, Alloy) — Опыт с SIEM или колончатыми СУБД (как ClickHouse) Условия: — Полная занятость — График: 5/2 — Формат работы: удалённо или гибрид или офис

Задачи: — Аналитическое сопровождение маркетинговых команд: предоставление рекомендаций, подготовка статистики и adhoc-отчетов — Поддержка и развитие системы сквозной аналитики для сайта и приложения — Аналитическая разметка действий на сайте и в приложении (совместно с продуктовым аналитиком) — Подготовка ТЗ для разработчиков на разметку — Поддержание и развитие коллтрекинга — Помощь команде маркетинга в проведении АБ-тестов — Проведение исследований, разработка рекомендаций для команды Требования: — Высшее образование — Опыт работы от 2 лет — Умение формулировать выводы и переводить их с языка аналитики на язык бизнеса — Структурное мышление и самостоятельность в работе — Умение работать с Яндекс.Метрика, Appmetrica, GTM, Google Analytics — Знание SQL (отчетность строится на данных из Clickhouse+MS SQL, визуализация в PowerBI/Superset) — Python (на уровне знания основных библиотек и умения собрать ETL-процесс в коде) Условия: — Профессиональное развитие в крупной MedTech компании — Оформление по ТК РФ с первого дня в дочернюю аккредитованную ИТ компанию — Гибридный формат работы: 2 дня удалённо и 3 дня офис, полной удалёнки нет — Полис ДМС с телемедициной, консультациями узких специалистов и психотерапевта — Корпоративные скидки до 50% на все виды медицинских услуг для вас и ваших близких — +3 дня оплачиваемых выходных — Подарок на День рождения и для детей к Новому году и Дню знаний — Внутреннее и внешнее обучение, семинары, тренинги — Корпоративные скидки и эксклюзивные специальные предложения от 800+ партнеров (товары, обучение, спорт, здоровье, рестораны, отдых) — Вознаграждение за рекомендацию друзей в команду ИНВИТРО — Корпоративные и спортивные мероприятия, профессиональные соревнования, конкурсы для сотрудников и членов семьи — Возможность профессионального и карьерного роста

Задачи: — Функциональное тестирование системы банка ACRM (аналитическая CRM) — Подготовка документов по тестированию на основе технических заданий (программ и методик испытаний (ПМИ), тест-кейсов, протоколов тестирования) — Регистрация и анализ ошибок, моделирование проблемных ситуаций — Проведение приёмо-сдаточных испытаний (ПСИ) — Взаимодействие с разработчиками и аналитиками — Актуализация и запуск автотестов на backend и frontend Требования: — Умение анализировать функциональные требования исходной документации — Навык проектирования тестовых сценариев — Опыт подготовки тестовых данных, необходимых в процессе тестирования (создания тестового окружения) — Умение анализировать результаты проведенного функционального тестирования на соответствие требованиям исходной документации — Опыт описания дефектов и проверки устраненных дефектов — Опыт оформления отчетности по результатам проведенного тестирования — Опыт создания и ведения тестовой документации — Знание процессов и циклов разработки программного обеспечения — Владение инструментами необходимыми для тестирования: DevTools, curl, Postman, SoapUI, WinSCP, DBeaver, Intellij IDEA — Достаточные знания в SQL (join нескольких объектов, основные агрегатные функции, union) — Написание простых скриптов sh/bash/cmd — Знание REST API — Опыт работы с базами данных PostgreSQL, ClickHouse, Oracle DB — Опыт тестирования в WebSocket-е, клиент-серверные приложения Условия: — График работы: 5/2 (пн-чт с 09:00 до 18:00, пт до 16:45) — Гибридный формат работы — Официальное оформление в соответствии с ТК РФ — Конкурентный уровень дохода — Доплата к отпуску и больничному листу — «Кафетерий льгот»: ДМС для работника и членов семьи, возмещение затрат на отдых, спортивные услуги, покупки на маркетплейсе «ПСБ Маркет» — Дополнительные льготы при заключении брака и рождении детей — Материальная поддержка в определенных жизненных ситуациях — Бесплатная программа поддержки работников: юридические, финансовые и психологические консультации, помощь в бытовых вопросах, автопомощь, корпоративные скидки, профориентация детей работников — Возможность профессионального развития и прохождения внутреннего и внешнего профессионального обучения — Корпоративная паритетная пенсионная программа

Location: United States; United Kingdom; Spain; Germany; The Netherlands Workplace: Remote ClickHouse is focused on growing a vibrant user community and becoming a Cloud-first company. We are looking for a Product Manager experienced in developing security features for ClickHouse. This is an exciting opportunity to work with a popular open-source project to extend and deepen its core capabilities and to develop cloud-native extensions that delight developers and data analysts across many use cases and market segments. If you are a doer with a “can do” mentality and a bias for action, we would love to hear from you. WHAT YOU WILL BE DOING: - Understand the real-time analytics and cloud database markets, competition, and technology trends in depth - Engage with the ClickHouse open-source user community and ClickHouse Cloud customers to understand current and aspirational use cases for ClickHouse core database - Distill and prioritize feature requests and issues into clear priorities for net-new capabilities and improvements - Work with engineering teams to scope and refine approaches to solving customer problems, both in the core database and in ClickHouse Cloud offerings - Set clear measurable goals around customer success, and use data-driven approaches to ensure new capabilities meet customer needs - Stay up-to-date on the state of the market and competitive landscape to identify needed features and areas of improvement for ClickHouse that align with the roadmap and general requests received by our community and customers - Work with partners to grow ClickHouse awareness and visibility WHAT YOU BRING ALONG: - Proven experience with database security principles and best practices - Knowledgeable and passionate about data engineering markets - data warehousing, data analytics, security, and observability - Strong vision around where these markets are headed, and what it takes to become a leader in this space - Previous experience with ClickHouse or a highly related OLAP technology at a deeply technical level - Previous experience with open-source projects, ideally as a product manager - Passionate about building enterprise capabilities that are powerful yet easy to use - Excellent written and verbal communication skills - Ability to influence multiple stakeholders without direct authority - Comfortable working with ambiguity and evolving based on business needs - Ability and desire to work with customers or community members, providing technical guidance and support during their POC. BONUS POINTS FOR: - Previous contributions to open-source projects - Engineering experience, ideally around distributed/cloud systems in C++ - Experience effectively working remotely in a global, distributed organization 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 eligible team member who joins our company receives equity. - 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: Melbourne Workplace: Remote The Role You’ll own a net-new enterprise territory in Melbourne. Most of your number comes from accounts that don’t buy from us yet. New business usually starts with a team already running ClickHouse — open source, or a Cloud account someone expensed — until a bill or a security review pushes the conversation up to the platform team and the budget owner. Common triggers: an Elasticsearch or Splunk bill that’s hard to defend, a warehouse that can’t serve a customer-facing feature fast enough, an AI product querying tens of billions of rows. You’ll carry a small set of existing accounts alongside the hunt, where growth comes from new teams inside an account that already buys from us. One team lands a workload, it works, and four other teams have a similar problem. But the bulk of this role is finding and opening accounts that aren’t on our map yet. What You Will Be Doing - Own the full sales cycle for new accounts in your territory — first conversation through security review, procurement, and close, on Cloud commitments and multi-year committed spend. - Build your own pipeline. Self-sourced outbound is the primary input to this territory, not a supplement to inbound. - Find and convert existing ClickHouse usage in new accounts. Unmanaged open-source deployments and self-serve Cloud accounts are the highest-yield source of new pipeline in this segment. - Multi-thread across the data platform team, the budget owner, security, and the executive sponsor rather than relying on a single champion. - Work with your Solutions Architect through the technical evaluation. They own the technical win, you own the commercial strategy and the close. - Run the procurement path: security questionnaires, legal redlines, vendor onboarding, and BYOC or private-deployment requirements, including Australian data residency where it’s required. - Give your champion the internal business case — TCO comparison against the incumbent, migration plan, and risk mitigation. - Grow the accounts you land by mapping the remaining teams and use cases and building an expansion plan against them. - Watch consumption trends across your accounts and engage early when usage flattens or spikes. Both are signals. - Keep Salesforce accurate and submit a forecast leadership can plan against. - Participate in the developer community in your territory: meetups, conferences, and events across Melbourne. What You Bring - 6+ years selling technical infrastructure to enterprise buyers — databases, data platforms, cloud infrastructure, observability, or developer tooling. - A track record of self-sourced pipeline. You can explain your weekly prospecting approach and what actually works for you. - Experience selling into Melbourne and Victorian enterprise accounts, and familiarity with how procurement and security review run here. - A track record closing complex deals that went through security review, legal, and procurement. - Enough technical fluency to hold an architecture conversation. You don’t need to write SQL, but you should be able to explain why a company moves a workload off Elasticsearch. - Experience with consumption-based or usage-metered commercial models, where revenue moves with usage between contract events. - Experience selling into developer-led, bottom-up adoption as well as top-down. - Ability to orchestrate people who don’t report to you — Solutions Architects, executive sponsors, partners, product managers. - Comfort building a territory from scratch rather than inheriting mature coverage. - Accurate forecasting, including when the number is bad. 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 eligible team member who joins our company receives equity. - 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.

Требования: — Уверенный опыт работы с данными на позиции аналитика от 4-5 лет — Опыт работы с аналогичным функционалом в Retail/FMCG в разрезе продаж, категорий — Приветствуется опыт работы в крупных компаниях производителях FMCG — Опыт работы с большими данными — Продвинутый уровень SQL и Excel, ClickHouse — Умение формировать SQL запросы без помощи нейронок — Опыт построения отчётности на базе справочников и аналитических агрегатов — Опыт постановки ТЗ для формирования отчётов — Умение находить оптимальные способы решения задачи (оптимально по скорости, затраченным ресурсам и работе с БД) — Интерес к профессии, желание развиваться и решать сложные задачи Задачи: — Работать с большим объемом данных — Разрабатывать логику аналитических выборок и отчётов — Работать с данными продаж, чеков, заказов, формировать агрегаты из транзакций, обогащать сырые данные — Писать сложные SQL запросы — Переводить бизнес-запросы в понятные технические задания для разработки отчётов, витрин — Работать с расхождениями в данных, находить и анализировать ошибки — Настраивать фильтры и метрики для BI Просьба указывать финансовые ожидания при отклике.

Задачи: — Работать с большим объемом данных — Разрабатывать логику аналитических выборок и отчётов — Работать с данными продаж, чеков, заказов, формировать агрегаты из транзакций, обогащать сырые данные — Писать сложные SQL запросы — Переводить бизнес-запросы в понятные технические задания для разработки отчётов, витрин — Работать с расхождениями в данных, находить и анализировать ошибки — Настраивать фильтры и метрики для BI Требования: — Уверенный опыт работы с данными на позиции аналитика от 4-5 лет — Опыт работы в Pharma - must — Опыт работы с большими данными — Продвинутый уровень SQL и Excel, ClickHouse (или другие колоночные БД) — Важно уметь формировать SQL запросы без помощи нейронок — Опыт построения отчётности на базе справочников и аналитических агрегатов — Опыт постановки ТЗ для формирования отчётов — Умение находить оптимальные способы решения задачи (оптимально по скорости, затраченным ресурсам и работе с БД) — Высшее образование — Гражданство и физическое местонахождение на территории РФ

Компания Centicore занимается продуктовой разработкой проектов Заказчиков под ключ. Вакансия Senior DevOps с удалённым форматом работы (РФ) и зарплатой 300 000-400 000 рублей на руки. Требования: — Опыт работы от 4-5 лет в эксплуатации высоконагруженных распределённых ИТ-систем. — Отличные знания Kubernetes. — Практический опыт настройки сетевых фабрик и Service Mesh (например, Istio, Linkerd). — Опыт развертывания, оптимизации и масштабирования open-source компонентов Observability: сборщики и CDC (Vector, Debezium, OpenTelemetry Collector). — Опыт работы с брокерами Apache Kafka (настройка кластеров, тюнинг партиций, управление квотами, обеспечение отказоустойчивости). — Навыки администрирования, горизонтального масштабирования и резервного копирования баз данных (реляционных и аналитических/временных рядов): VictoriaMetrics, ClickHouse, Elasticsearch. — Уверенное владение инструментами Infrastructure as Code (Terraform / OpenTofu, Ansible). — Опыт построения CI/CD пайплайнов (GitLab CI, ArgoCD). — Уверенное владение Bash/Shell. — Хорошие навыки автоматизации рутинных задач на Python или Go. Условия: — Удалённый формат работы в IT аккредитованной компании. — Длительный проект. — Оплачиваемый отпуск 28 календарных дней в год и оплачиваемые больничные. — Предоставление техники (MAC, Windows). — ДМС со стоматологией. — Компенсация хобби/спортзала/английского языка. — Компенсация профессионального обучения. — Возможность участия во внутренних программах компании и активностях, например, в реферальной программе «приведи друга». — Онлайн и оффлайн корпоративные мероприятия (йога, шахматы, покер, квиз, марафон, CS2 и др.). — Программа лояльности Сентибонусы за проявление активностей, стаж работы и др.. — Оформление по ТК.

Задачи: — Разрабатывать и поддерживать ETL процедуры в Airflow — Проектировать, реализовывать и внедрять распределённые системы обработки и хранения данных — Участвовать в развитии архитектуры хранилища — Работать с реляционными/NoSQL базами данных — Разрабатывать и поддерживать процедуры автоматизации аналитической инфраструктуры Требования: — Уверенное знание SQL — Уверенное знание Python — Опыт разработки ETL процедур от 3-х лет — Опыт работы с реляционными СУБД — Навыки командной разработки в Git Будет плюсом: — Современные code-driven ETL/ELT инструменты — Распределенные колоночные СУБД (ClickHouse, Vertica, Greenplum) — Docker, Kubernetes — S3 хранилище — CI/CD процедуры Условия: — Полная занятость — График 5/2 — Формат работы: удалённо

Задачи: — Разработка backend-реализаций веб-сервисов — Участие в разработке архитектуры и реализации прототипов новых веб-сервисов — Коммуникация с front-end и back-end разработчиками, QA — Написание валидного читабельного кода — Написание юнит-тестов для разработанных компонентов — Проведение код-ревью Требования Hard Skills: — Django, Django REST Framework, FastAPI — asyncio, asyncpg — PostgreSQL: проектирование, оптимизация запросов — ClickHouse, Apache Kafka — Docker, Docker Compose, Kubernetes (базово: деплой, конфиги, секреты, логи) — GitLab CI/CD, Gitflow, опыт code review Требования Soft Skills: — Командное взаимодействие Будет плюсом: — Опыт Fullstack-разработки (React / TypeScript) — большой плюс

Location: Canada (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity and we're interested in candidates based in the US or Canada. Residents of Quebec are not eligible for this role. Senior Full-Stack Software Engineer, Grafana Data Source Plugins The Opportunity: As a Senior Full-Stack Engineer in the Grafana Data Source Plugins squad, you will take a leading role in developing and enhancing a diverse portfolio of data source plugins that retrieve the data powering Grafana dashboards used by teams worldwide. Our team focuses on continuously improving data source plugins, ensuring seamless experience for human and agent users alike. A key aspect of this role is guaranteeing the smooth operation and reliability of our plugins in the Grafana Cloud, helping us deliver on our commitment to world-class observability tools. What You’ll Be Doing: Some data source plugins we own: Prometheus, Loki, Infinity, MySQL, PostgreSQL, AWS Cloudwatch, and Clickhouse.  The full catalog is listed here . A typical “day in the life” could include: Building or improving Grafana plugins to integrate third party services or databases into Grafana Supporting the operations and reliability of our plugins in Grafana Cloud Coming up with suggestions for process improvements Integrating data sources with agentic workflows such as Grafana Assistant Providing technical support in customer escalations Working closely with the rest of the Grafana Division What Makes You a Great Fit: You know how to transform ideas into working code, you are able to design a solution, get feedback and deliver large projects. You are a self-driven individual who understands the power of feedback loops in making roadmap decisions and driving our product forward. You are a motivated self starter with a bias towards action, and willing to take on any challenge You are customer focused. We build everything with our users in mind. You have a passion for creating intuitive products that fit customers’ needs. You are an excellent communicator and you enjoy collaboration You are comfortable working in a remote-first company Requirements: Solid experience with Golang & Typescript Experience with Kubernetes & microservices Experience writing clean, robust, and performant software that is easily maintained by others Experience participating in an on-call rotation and performing operations/SRE tasks Bonus Points For: You have been a user of Grafana and Grafana Data Sources You have expertise in one of the underlying databases we support You have strong experience working with a Product Manager or external stakeholders In the United States, the Base compensation range for this role is CAD 170,247 - $204,297 .  Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . #LI-Remote #LI-Remote *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: United States (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity and we're interested in candidates based in the US or Canada. Residents of Quebec are not eligible for this role. Senior Full-Stack Software Engineer, Grafana Data Source Plugins The Opportunity: As a Senior Full-Stack Engineer in the Grafana Data Source Plugins squad, you will take a leading role in developing and enhancing a diverse portfolio of data source plugins that retrieve the data powering Grafana dashboards used by teams worldwide. Our team focuses on continuously improving data source plugins, ensuring seamless experience for human and agent users alike. A key aspect of this role is guaranteeing the smooth operation and reliability of our plugins in the Grafana Cloud, helping us deliver on our commitment to world-class observability tools. What You’ll Be Doing: Some data source plugins we own: Prometheus, Loki, Infinity, MySQL, PostgreSQL, AWS Cloudwatch, and Clickhouse.  The full catalog is listed here . A typical “day in the life” could include: Building or improving Grafana plugins to integrate third party services or databases into Grafana Supporting the operations and reliability of our plugins in Grafana Cloud Coming up with suggestions for process improvements Integrating data sources with agentic workflows such as Grafana Assistant Providing technical support in customer escalations Working closely with the rest of the Grafana Division What Makes You a Great Fit: You know how to transform ideas into working code, you are able to design a solution, get feedback and deliver large projects. You are a self-driven individual who understands the power of feedback loops in making roadmap decisions and driving our product forward. You are a motivated self starter with a bias towards action, and willing to take on any challenge You are customer focused. We build everything with our users in mind. You have a passion for creating intuitive products that fit customers’ needs. You are an excellent communicator and you enjoy collaboration You are comfortable working in a remote-first company Requirements: Solid experience with Golang & Typescript Experience with Kubernetes & microservices Experience writing clean, robust, and performant software that is easily maintained by others Experience participating in an on-call rotation and performing operations/SRE tasks Bonus Points For: You have been a user of Grafana and Grafana Data Sources You have expertise in one of the underlying databases we support You have strong experience working with a Product Manager or external stakeholders In the United States, the Base compensation range for this role is USD $ 167,143 - $200,572 .  Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . #LI-Remote #LI-Remote *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .