Вакансии

Ищем начинающего DevOps-инженера с перспективой профессионального роста внутри команды. Задачи: — поддержка Linux-серверов и CI/CD — работа с Docker и GitLab Runner — автоматизация инфраструктуры с помощью Ansible — настройка мониторинга, сетей и внутренних сервисов Стек: Linux, Docker / Docker Swarm, GitLab CI/CD, Ansible, Traefik, PostgreSQL, Prometheus, Grafana, Loki, NetBird. Впереди переход на Kubernetes. Рассматриваем DevOps-инженеров с опытом до одного года, а также кандидатов без коммерческого опыта. От кандидата ожидаем базовое знание Linux, сетей, Docker и Git, готовность самостоятельно разбираться в задачах и задавать вопросы. Опыт с остальными инструментами необязателен — поможем освоить их в процессе работы. Что предлагаем: — Небольшой, но дружный коллектив — Полностью удалённая работа из любой страны — Гибкая система оплаты.

ASOS.com — британский онлайн‑ритейлер модной одежды, обуви, аксессуаров и косметики. В компании работают русскоговорящие ребята. Технологии и инструменты: SQL, Databricks, Spark, DBT, Python, Mixpanel, Adobe и другие. Компания основана фаундерами Nick Robertson, Andrew Regan, Quentin Griffiths, Deborah Thorpe. Размер команды: 1k-5k человек. Инвестиции: £587.5M.

Задачи: — Администрировать, поддерживать и оптимизировать облачные платформы и инфраструктуру. — Настраивать, конфигурировать, поддерживать и совершенствовать CI/CD- и GitOps-пайплайны. — Внедрять и поддерживать практики Infrastructure as Code (IaC) с использованием таких инструментов, как Ansible, Terraform, Pulumi. — Управлять контейнеризированными средами с использованием Docker, Docker Swarm и Kubernetes. — Обеспечивать надежную инфраструктуру и процессы развертывания для BI-сервисов и приложений, включая ClickHouse, SQL, Airflow, Tableau, Superset. — Тесно взаимодействовать с командами разработки и BI для повышения надежности развертывания, консистентности окружений и операционной эффективности. Требования: — Уверенные навыки настройки и администрирования как минимум одной облачной платформы. — Уверенные навыки построения и автоматизации процессов развертывания с использованием CI/CD и GitOps. — Опыт построения масштабируемой IT-инфраструктуры. — Уверенные навыки настройки Linux-серверов и устранения неисправностей. — Практический опыт работы с Kubernetes. — Понимание сетевой модели OSI. — Понимание принципов построения надежной и масштабируемой инфраструктуры, а также автоматизированных процессов развертывания. — Знание принципов информационной безопасности и защиты данных. — Интерес к работе с инфраструктурой для Business Intelligence и data-related решений либо соответствующий практический опыт.

Задачи: — Отвечать за всю AI-часть продукта: архитектура AI-системы от выбора LLM-моделей до построения RAG-pipeline и интеграции компьютерного зрения, принимать все ключевые технические решения — Обеспечивать качество рекомендаций, повышая конверсию на каждой итерации — Проводить быстрые итерации с выкатыванием изменений каждую неделю, сбором метрик, анализом и улучшением — Проводить эксперименты: A/B тесты промптов, гибридный поиск (текст + визуал + отзывы), мультимодальные модели, быстро проверять гипотезы на реальных пользователях — Масштабировать систему с 2000 туров на Мальдивы до 50,000+ туров по трём направлениям с тысячами запросов в день — Строить продукт с нуля, быстро экспериментировать и влиять на архитектуру Требования: — Опыт с продакшен LLM-приложениями, построение RAG-систем или чат-ботов на основе GPT/Claude — Экспертный уровень промпт-инжиниринга: правильная структура промптов, few-shot examples, chain-of-thought — Опыт работы с эмбеддингами и векторным поиском, понимание similarity search, hybrid search, reranking — Python на уровне продакшена: чистый, быстрый, поддерживаемый код Будет плюсом: — Опыт с компьютерным зрением и мультимодальными моделями (CLIP, GPT-4o, Claude 4.5 Sonnet) — Опыт с high-load системами и оптимизацией latency — Понимание рекомендательных систем — Понимание MLOps: мониторинг моделей, версионирование, A/B тестирование — Опыт построения recommendation систем и MCP для LLM систем — Личный опыт использования LLM для автоматизации задач Софт-скиллы: — Продуктовое мышление: AI как инструмент решения бизнес-задач — Умение работать с метриками: конверсия, время сессии, escalation rate — Быстрота принятия решений: выкатывать несовершенное решение и тестировать — Умение объяснять сложное простым языком для команды и бизнеса Условия: — Официальное оформление по ТК РФ — График 5/2, офис, сокращённый рабочий день по пятницам до 15:30 — Корпоративные программы обучения и развития — Медицинское обслуживание: ДМС и собственная медсанчасть — Специальные предложения от компаний-партнеров (рестораны, магазины, отдых, мероприятия) — Организация отдыха сотрудников и их детей, оплата детского сада — Аккредитованная IT компания — Офис на станции м. Курская — Корпоративные условия на приобретение туров — Дополнительный оплачиваемый отпуск 3 дня, оплата больничного — ДМС для членов семьи по корпоративным условиям — Корпоративные условия на изучение английского и занятия спортом

Location: Warsaw Workplace: OnSite ROLE HIGHLIGHTS: - Title: AIT Engineer – Optical Systems - Department: Global Manufacturing Organization - Reports to: Head of MAITE, Optics - Location: Warsaw, Poland - Type of Contract: Permanent - Working model: On-site - Employment is subject to applicable security screening (incl. SUPO, where required) ABOUT THE ROLE ICEYE is seeking an AIT Engineer to support the assembly, integration, and testing of satellite systems, including the integration of optical payloads into the spacecraft platform. This is a hands-on technical role in an early-stage production environment, where systems are still evolving and processes are not yet fully defined. You will work directly with flight hardware in cleanroom conditions, supporting the assembly, integration, and testing of the satellite bus, as well as the integration and validation of optical payloads provided by external suppliers. You will contribute to bringing the full satellite system from design into production, ensuring that optical payloads are successfully integrated with the satellite platform (bus), and that the system can be built, tested, and scaled reliably. This includes supporting troubleshooting and continuous improvement during production ramp-up. WHO WE ARE ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth. ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system. ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future. Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific. WHAT YOU WILL DO - Execute assembly, integration, and testing (AIT) of satellite subsystems and optical payloads - Perform optical alignment and integration activities (focus, tilt, centering, boresight) using precision equipment - Conduct hands-on inspection, assembly, and verification of satellite hardware in cleanroom environments - Support integration of externally supplied optical payloads into the satellite system - Identify, contain, and drive root cause analysis of non-conformances; implement corrective actions and feedback into design and production processes - Define and execute test and verification activities, including integration and acceptance testing at subsystem and system level - Support optical and system-level performance validation - Define, develop, and maintain process plans, procedures, and technical documentation, supporting implementation and continuous improvement of manufacturing and integration processes - Contribute to AIT process definition and improvement, enabling scalable production - Interface with optical, mechanical, and electrical engineering teams to ensure system-level integration - Collaborate with external suppliers during payload integration and validation - Support setup of tooling, fixtures, and test setups (GSE) required for production - Apply system-level understanding to anticipate integration risks across subsystems and ensure successful builds WHAT WE’RE LOOKING FOR MUST HAVE - 3+ years of hands-on experience in integration, testing, or production of complex hardware systems, with relevant experience in optical systems, optomechanics, physics, or other high-precision hardware - Hands-on experience with optical systems integration and alignment (focus, tilt, centering, boresight) - Experience working with optical payloads or Earth Observation systems - Familiarity with optical metrology tools (e.g. interferometers, collimators, optical benches, MTF setups) - Good system-level understanding across multiple disciplines (optical, mechanical, electrical) - Experience working with precision hardware in cleanroom environments - Experience working in structured production environments (e.g. MES or similar systems) - Strong troubleshooting skills with structured root cause analysis - Ability to analyze and interpret test data to support integration and validation activities - Experience developing or working with process plans and technical documentation - Ability to work in fast-paced and evolving production environments - Proactive, hands-on approach to problem-solving - Strong written and spoken English communication skills NICE TO HAVE - Experience supporting environmental testing (e.g. thermal vacuum, vibration) - Experience working with external suppliers or partners - Experience supporting systems from prototype through production ramp-up - Experience working in lean manufacturing or continuous improvement environments APPLICATION PROCESS - Talent Acquisition Interview - Hiring Manager General Interview - Technical Interview (onsite or virtual), including a Technical Challenge - Hiring Team + Director-level Interview - Offer Decision WORKING AT ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. HOW WE WORK (OUR VALUES) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions. - See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters—and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. BENEFITS Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. Base salary range for this position is dependent on experience, and will be negotiated individually. OUR COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us—we’ll do our best to help. Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com http://iceye.com.

Ищем Full-Stack QA Engineer, который умеет работать как с ручным тестированием, так и с автоматизацией. Важная часть роли — тестирование web и API, взаимодействие с разработчиками, анализ изменений и активное использование AI-инструментов в работе. Задачи: — Ручное тестирование веб-приложения и API. — Разработка, актуализация и поддержка тест-кейсов и тест-сьютов в Zephyr. — Анализ требований и изменений, определение объёма и приоритетов тестирования. — Функциональное, регрессионное, интеграционное и API-тестирование. — Анализ дефектов, создание баг-репортов и работа с backlog в Jira. — Подготовка test reports по результатам тестирования. — Взаимодействие с разработчиками на всех этапах разработки. — Участие в Agile-процессах: daily, refinement, review/demo, retrospective. — Разработка и поддержка автоматизированных тестов. — Соотношение ручного и автоматизированного тестирования — ориентировочно 70/30. — Активное использование AI-инструментов в ежедневной работе. Требования: — От 3 лет опыта в QA / Software Testing. — Практический опыт тестирования web-приложений и API. — Опыт работы в Agile-командах. — От 1 года опыта в автоматизации тестирования. — Практический опыт работы с Python, pytest, Playwright, requests, Allure. — Опыт работы с AI инструментами: Claude, Claude Code или аналогами. — Опыт работы с Jira / Zephyr - работа с backlog и дефектами, создание и поддержка test cases и test cycles. — Уверенное знание и применение техник тест-дизайна. — Понимание метрик тестирования. — Уверенное понимание HTTP, REST и принципов работы API, понимание GraphQL. — Уверенное владение Python и инструментами автоматизации тестирования pytest, Playwright, requests. — Умение анализировать результаты автотестов в Allure. — Уверенное владение Chrome DevTools и инструментами для тестирования API: Postman, Insomnia, curl, Swagger. — Уверенное знание SQL. — Умение пользоваться терминалом. — Понимание основных Git-процессов и умение работать с merge conflicts. — Опыт работы с системами логирования и мониторинга: Grafana, Sentry, Splunk или аналогами. — Внимательность к деталям, ответственность, самостоятельность, проактивность, коммуникабельность, умение работать в команде. — Применение risk-based testing для определения приоритетов и объёма тестирования. — Понимание принципов shift-left testing. — Умение анализировать влияние изменений и определять необходимый regression scope. — AI-first подход к тестированию: использование AI для анализа изменений, создания и актуализации тест-кейсов, разработки и улучшения автотестов. Языковые требования: — Английский язык — B1+: чтение технической документации, написание баг-репортов, рабочая коммуникация с командой.

Требования: — 2+ года опыта работы Data Analyst, Data Engineer или Analytics Engineer — Сильные навыки SQL и опыт работы с PostgreSQL или другими реляционными базами данных — Опыт построения и поддержки ETL/ELT пайплайнов — Владение Python для обработки данных и автоматизации — Понимание моделирования данных и концепций хранилищ данных — Опыт работы с большими наборами данных и оптимизации запросов — Свободное владение английским языком Условия: — Поддержка релокации — Полная занятость — Конкурентная зарплата — Работа в офисе в Лимассоле Задачи и подробности не указаны.

Location: Warsaw, Mazowieckie, Poland; Sofia City, Bulgaria; Limassol, Cyprus Workplace: hybrid Capital.com's Product Security team protects our web and mobile applications, infrastructure, and external perimeter in a highly regulated environment. As Senior/Staff Application Security Engineer, you will raise the bar for application security across the organisation. This role is measured by leverage: how well you design, automate, and scale security processes so that many engineering teams can build securely by default. You will lead security architecture reviews and threat modelling, increasingly with the help of AI tooling, and turn one-off security work into repeatable, self-service capabilities. The role combines deep hands-on offensive and defensive security expertise with the engineering mindset needed to automate at scale. You will work closely with development, QA, DevOps, and platform teams. Responsibilities: Security Architecture & Threat Modelling: Lead security architecture reviews and threat modelling for new and existing systems, using AI tools to make reviews faster, more consistent, and scalable across teams Act as a security force multiplier by influencing the standards, patterns, and guardrails that let teams move fast and stay secure Security Automation & Tooling: Design, build, and automate scalable security processes that engineering teams can self-serve, covering secure design review, threat modelling, testing, and remediation workflows Integrate and automate security checks across the SDLC and CI/CD pipelines (SAST, DAST, SCA, secrets, and IaC scanning), tuned for strong signal and low friction Own and evolve security tooling such as DefectDojo and SAST, DAST, and SCA platforms, maximising automation, coverage, and integration Apply AI and LLM-based tooling to architecture review, threat modelling, code review, and vulnerability triage, and help define how the team adopts these tools safely Security Testing & Vulnerability Management: Conduct and oversee security assessments of web and mobile applications, APIs, and cloud infrastructure, including manual testing and PoC development Run vulnerability scans across internal infrastructure and the external perimeter, then analyse findings, define remediation, and track issues to closure Support and triage the Bug Bounty Program and external vulnerability reports, automating triage where possible Participate in and help lead red teaming and offensive security exercises Enablement: Drive knowledge sharing on secure development, mentor engineers, and deliver training for development and QA teams Requirements: Experience: 5+ years in application or product security, or equivalent depth, with a track record of senior or staff-level impact Demonstrable experience leading security architecture reviews and threat modelling (e.g. STRIDE, attack trees, data-flow analysis) across multiple teams or products Proven ability to automate and scale security processes by building tooling, integrations, and self-service workflows that reduce manual effort Technical: Strong hands-on security testing skills, including code review and web, mobile, and API application security assessments, as well as the ability to triage and validate external vulnerability reports and bug bounty submissions Strong software engineering ability in at least one language (e.g. Python, Go, JavaScript), with the ability to build automation, not just scripts Deep understanding of the OWASP Top Ten, secure design, and secure coding best practices Experience with SAST, DAST, SCA, and vulnerability management platforms, and integrating them into CI/CD Strong understanding of modern application architectures: REST APIs, microservices, cloud-based systems, and containers Practical experience applying AI and LLM tooling to security work, or clear enthusiasm and aptitude to do so Collaboration: Excellent communication and influencing skills: you can explain security concepts to technical and non-technical stakeholders and drive change without direct authority A self-starter who enjoys solving complex problems, building leverage through automation, mentoring others, and strengthening security culture Nice to have: Experience securing the AI harness: hardening LLM and agent pipelines, prompts, tool and MCP integrations, and model endpoints against prompt injection, data leakage, and insecure agent actions Experience securing Kubernetes, including cluster hardening, RBAC, network policies, admission control, workload isolation, and image and supply-chain security Experience securing AWS infrastructure, including IAM, network and account architecture, key and secret management, and CSPM Experience building AI-assisted security tooling or internal self-service security platforms Experience mentoring or technically leading a security team Offensive or advanced security certifications such as OSAI, OSEP, OSCP, or OSWE What you'll get in return: You will join the company, that cares about work and life balance Annual Bonus based on the performance review cycle Generous Annual Leave Policy Medical Insurance and Pension fund, with additional benefit packages based on the location Hybrid working model (3 days from our modern office and 2 days fully remotely) Comprehensive Workation Policy with 30 more remote days available. Possibility of taking two additional days of paid leave per year to dedicate to volunteering efforts.

Location: Limassol, Cyprus Workplace: on-site Mayflower is a technology company building high-load products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience. We are looking for a Lead ML Engineer to own a new ML stream focused on fast delivery of applied machine learning solutions across different product and business domains. The stream will work with a broad range of ML challenges. Some initiatives may be relatively small and delivered within a few weeks, while others may prove their value and grow into larger dedicated projects. This role combines hands-on ML engineering with end-to-end technical delivery ownership. You will receive product problems and expected outcomes from Product or internal stakeholders, clarify the technical requirements and constraints, define the implementation approach, coordinate execution within the stream, and bring solutions to production readiness and launch. This is a highly hands-on role. The stream will not have a dedicated software engineer for every initiative, so we expect Data Scientists and ML Engineers to be comfortable working beyond experimentation and contributing directly to production code. The role is not tied to a single ML domain. We value strong ML fundamentals, engineering skills, pragmatism, and the ability to quickly understand new problem areas more than deep specialization in one particular class of models. Job Responsibilities Technical Delivery Ownership Turn product and business problems into concrete ML implementation plans. Clarify requirements, constraints, available data, integrations, and success criteria together with Product and relevant stakeholders. Define technical scope, milestones, dependencies, risks, and delivery estimates. Select appropriate ML approaches and determine the fastest reliable way to validate and implement them. Drive technical delivery through experimentation, implementation, integration, deployment, and launch readiness. Keep delivery on track, proactively identify blockers, and coordinate dependencies with other teams. Provide Product with clear technical options, trade-offs, estimates, risks, and experiment results required for product decisions. Support production rollout and iteration based on observed results. Hands-on ML & Engineering Design, train, evaluate, and deploy ML models across different domains and problem types. Write production-quality Python and contribute directly to implementation. Build APIs, batch jobs, data-processing pipelines, and ML services required to deliver solutions where appropriate. Work with classical ML, deep learning, and foundation-model-based approaches depending on the problem. Process and transform large production datasets using Python and SQL. Integrate models into existing production systems. Implement appropriate testing, monitoring, logging, and observability for delivered ML solutions. Work within the shared ML infrastructure, architecture, and engineering practices used across the company. Collaborate with Data Science, Backend, Data Engineering, and MLOps specialists when deeper domain expertise or infrastructure changes are required. Stream Execution Break initiatives down into concrete technical tasks and coordinate execution within the stream. Coordinate the work of Data Scientists and ML Engineers contributing to stream initiatives. Review technical approaches, experiments, and implementation. Keep the team focused on the agreed scope, priorities, and delivery timeline. Identify technical risks and dependencies early and drive them to resolution. Escalate architectural, infrastructure, or methodological questions when broader alignment is required. Help prepare successful initiatives for scaling or transition into longer-term ownership if they grow beyond the scope of the stream. Cross-functional Collaboration Work closely with Product throughout the delivery lifecycle. Independently gather the technical details and constraints required to execute on a product request. Communicate estimates, dependencies, technical trade-offs, and delivery status clearly. Work directly with Engineering and other internal teams to unblock implementation. Challenge technically unclear, contradictory, or infeasible requirements and propose practical alternatives. You’ll thrive here if you have 5+ years of commercial experience in Machine Learning, Data Science, or ML Engineering. Strong hands-on Python programming and software engineering skills. Experience taking ML solutions from a product requirement through experimentation, implementation, integration, and production. Strong understanding of machine learning methods, statistics, experimentation, and model evaluation. Experience writing maintainable production code rather than working exclusively in notebooks. Experience building APIs, services, batch processing, or data pipelines. Strong SQL skills and experience working with large production datasets. Practical experience with Docker and production deployment environments. Ability to turn partially defined problems into concrete technical plans. Ability to estimate work, identify dependencies and risks, and drive technical execution against a timeline. Experience owning technical delivery involving several contributors and coordinating work across dependencies. Experience reviewing code and technical approaches. Ability to work effectively within established engineering and ML practices while independently owning delivery within a stream. Strong communication skills and the ability to work directly with Product and technical stakeholders. Ability to balance speed and engineering quality: validate ideas quickly when uncertainty is high and build robust solutions when moving towards production. Nice to Have Previous experience as a Tech Lead, Stream Lead, or technical owner of ML initiatives. Experience with Kubernetes and CI/CD. Experience with Kafka or other streaming platforms. Experience with Airflow, MLflow, experiment tracking, model monitoring, or similar tooling. Experience building real-time or high-load ML services. Experience with FastAPI or similar Python service frameworks. Experience across several ML domains, such as recommendation systems, ranking, NLP/LLMs, Computer Vision, anomaly detection, forecasting, or classification. Experience with LLM inference, fine-tuning or other GenAI systems. Experience in teams where Data Scientists and ML Engineers own a substantial part of production implementation themselves.

Задачи: — Создание и поддержание актуальной тестовой документации (тест-планов, тест-кейсов, чек-листов, тестовых сценариев). — Определение критериев приемки и требований к тестированию на основе пользовательских историй и спецификаций. — Проведение функционального, регрессионного, интеграционного и приемочного тестирования. — Тестирование web приложений или десктопных. — Тестирование взаимодействия с базами данных (Oracle, PostgreSQL). — Тестирование систем очередей сообщений (RabbitMQ). — Тестирование API (REST, SOAP) с использованием инструментов Postman, Swagger и т.п. — Анализ результатов тестирования, выявление, документирование и классификация дефектов в системе отслеживания ошибок. — Участие в обсуждении найденных дефектов с разработчиками и аналитиками. — Предложение улучшений и новых тестов на основе анализа результатов. — Активное взаимодействие с разработчиками, бизнес-аналитиками, DevOps и другими участниками проекта для уточнения требований и решения вопросов возникающих в процессе тестирования. — Участие в ежедневных стендапах, планировании спринтов и ретроспективах. Требования: — Опыт тестирования web приложений. — Знание SQL и опыт работы с базами данных (Oracle, PostgreSQL): умение писать запросы для проверки и подготовки данных. — Опыт работы с системами очередей сообщений (RabbitMQ или аналоги). — Опыт тестирования API (REST, SOAP) с использованием инструментов Postman, Swagger и т.п. — Опыт работы с системами управления проектами и отслеживания задач (Jira, Confluence, Azure DevOps, Яндекс Трекер, Trello и т.п.). — Глубокое понимание процессов, методологий и инструментов тестирования. — Опыт разработки тестовой документации: тест-кейсы, чек-листы, тест-планы. — Владение техниками тест-дизайна (граничные значения, классы эквивалентности, pairwise testing и т.п.). — Аналитические способности и умение выявлять причины дефектов. — Критическое мышление и навыки решения проблем. — Отличные коммуникативные навыки (устные и письменные) и умение работать в команде. Условия: — Трудоустройство в соответствии с ТК РФ. — Компания имеет аккредитацию в сфере информационных технологий. — Полностью дистанционный формат работы, открыты для соискателей из любой точки. — Обеспечение необходимым техническим оснащением для работы. — Полный социальный пакет. Этапы отбора: — Первичное телефонное интервью. — Онлайн-собеседование. — Решение.

Мы в AnySense создаем AI-систему для автоматизацию административных процессов в американском healthcare секторе (с фокусом на автоматизацию работы страховых на US рынке). Задачи: — Разработка и оптимизация Python-бэкенда — Архитектура микросервисов и API (LLM, OCR/CV, клиент и админки) — Создание пайплайнов для LLM-агентов — Интеграция и поддержка OCR и CV-модулей — Тюнинг LLM, работа с датасетами и метриками в проде — Автоматизация процессов через RPA — Поддержка CI/CD и DevOps-процессов Требования: — Понимание архитектуры, системного дизайна и API — Уверенный опыт с Python (4+ лет) — Опыт с LLM-агентами, OCR/CV или похожими AI-модулями — Prompt engineering, тюнинг LLM и датасеты — Понимание / применение RPA — Опыт с CI/CD, Docker, продакшен-развёрткой Бонус: опыт в healthcare и AI-комплаенсе Условия: — USD 6000-10000 / мес — Remote (timezone +-2-3 часа от CET) — Офлайн-встречи несколько раз в год (EU, другие локации) — Работа в core team c founder’ом и СTO.

Location: Belgrade, Serbia; Berlin, Germany; Limassol, Cyprus; Madrid, Spain; Munich, Germany; Paphos, Cyprus; Prague, Czech Republic; Remote, Germany; Warsaw, Poland; Yerevan, Armenia Are you a QA Engineer who cares about code craft and system stability? Do you want to focus on quality over quick fixes and own your decisions from day one? About JetBrains We create intelligent software development tools for developers and teams. More than 15 million users, over 300,000 companies, and 88 of the Fortune Global Top 100 rely on our products to solve real, complex problems. Our mission is simple: make development teams more productive and AI adoptable at scale. What you’ll do IntelliJ IDEA changed how Java development worked by introducing automated refactoring, and it remains a core tool for thousands of developers worldwide. Within the IntelliJ IDEA Ultimate team, we focus specifically on improving how the IDE supports key JVM frameworks like Spring, Jakarta EE, and Hibernate. We need an independent QA Engineer to help us ensure these enterprise development tools remain reliable and efficient. You will take ownership of the testing process for new and existing functionality, balancing manual exploratory testing with automated test development. You will work closely with developers to spot flaws early and collaborate directly with product managers to decide which issues impact our users most. Day to day, you will: Perform exploratory testing of new and existing features to uncover edge cases. Run regression tests to ensure platform stability before releases. Maintain, write, and scale our automated test suites. Reproduce user-reported issues and provide technical support to resolve them. Collaborate with developers to share product knowledge and diagnose system bugs. Work with product managers to estimate the priority and business impact of issues. What you’ll bring Strong communication skills and the ability to explain technical problems clearly. Independence, self-discipline, and a habit of learning new technologies on your own. A collaborative approach to working with distributed engineering teams. What you’ll need Proven experience testing commercial software applications. Proficiency in Java or Kotlin sufficient to write test applications and read source code. Fluency in spoken and written English. Practical familiarity with build tools (like Maven, Gradle, or Bazel), databases, and Docker containers. Experience testing software across different operating systems alongside basic system administration skills. What success looks like Success in this role means earning the trust of your team through sound testing decisions and leaving our codebase cleaner and more stable than you found it. You will move past simple task lists to take real ownership of product quality, helping the team ship reliable updates without compromising speed. Ultimately, success is defined by preventing regressions and ensuring enterprise developers have a seamless experience using our tools. Why join JetBrains? Strong base salary. We offer competitive pay that reflects your skills and experience. Flexible work location. Enjoy the freedom to work from home or from the office. Remote work. Spend up to 30 days per year working remotely from abroad. Extra time off. More days to relax, recharge, and do the things you love. Medical insurance allowance. Enjoy peace of mind for you and your family Learning and development opportunities. Access to conferences, courses, and language classes. Relocation support. We help make your move as smooth and stress-free as possible. Language classes. Pick up the local language or sharpen your English skills. Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays. Mental health support. To help you feel your best, we provide easy access to professional mental health services. Sports benefit. Enjoy an on-site gym or sports club stipend. Internal events. Join company-wide celebrations and team gatherings. *Some benefits may vary depending on location. #LI-DNI We are an equal opportunity employer We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation. We process the data provided in your job application in accordance with the Recruitment Privacy Policy.

Задачи: — Участвовать в техническом дизайне и архитектурных решениях, наставлять инженеров и способствовать межфункциональному сотрудничеству — Руководить и участвовать в нескольких проектах одновременно, балансируя владение ключевыми инициативами и поддержку команды — Создавать и поддерживать надежные, низколатентные API и бэкенд-сервисы для платформ Trust and Safety — Стать экспертом в архитектуре платформы, предоставлять технические решения для совершенствования платформ — Сотрудничать с дата-инженерами, аналитиками и менеджерами продуктов для выпуска функций, улучшающих защиту и опыт пользователей — Повышать надежность и производительность платформы через архитектуру, практики наблюдаемости и автоматизацию — Развивать возможности экспериментов, жизненного цикла политик и интеграции ML для поддержки более умных и быстрых решений в масштабе — Участвовать в ротации дежурств, включая реагирование на инциденты вне рабочего времени при необходимости Требования: — Опыт разработки ПО в продакшене на масштабируемых системах не менее 5 лет — Опыт технического лидера в команде и на сложных проектах, включая архитектурные решения и координацию команд — Опыт работы с Ruby on Rails или аналогичными фреймворками — Опыт работы с транзакционными базами данных и системами кэширования — Глубокое понимание архитектурных паттернов для масштабных веб-приложений — Умение наставлять инженеров и развивать команду — Ценность поддерживаемого и хорошо протестированного кода — Интерес к глубокому изучению архитектур систем и технических вызовов — Опыт работы в динамичной или стартап-среде будет преимуществом Условия: — Гибридный формат работы: 4 дня в офисе в Сан-Франциско, пятница — удаленно — Полный рабочий день — Бонусы, конкурентный пакет акций и социальные гарантии — Медицинские, финансовые и благополучные бенефиты — Щедрая политика отпусков и оплачиваемых выходных — Поддержка семейных нужд, включая оплачиваемый декретный отпуск и компенсации — Возможность работать в опытной команде в сфере финтеха Компания Chime — финтех-компания, не банк, предоставляющая удобные банковские инструменты для финансового прогресса пользователей.

Задачи: — Тестирование хранилища данных — Проверка полноты, согласованности и точности данных — Валидация преобразований данных по принципу source-to-target — Проведение регрессионного тестирования — Анализ результатов тестирования и выявление дефектов — Автоматизация тестовых проверок на Python / PyTest — Работа с большими объёмами данных — Взаимодействие с разработчиками и системными аналитиками — Работа с Jira, Confluence, Git и инструментами DWH Требования: — Высшее экономическое или математическое образование — Опыт работы в QA от 1.5 лет, включая тестирование хранилищ данных — Понимание архитектуры DWH: схемы «звезда», «снежинка», Data Vault — Знание PL/SQL, Oracle, Python — Понимание методик тестирования хранилищ данных — Опыт проверки полноты, согласованности и точности данных — Опыт валидации преобразований source-to-target — Опыт регрессионного тестирования — Навыки автоматизации тестов на Python / PyTest — Аналитический подход и внимание к деталям при работе с данными — Умение работать с большими объёмами информации — Коммуникация с разработчиками и аналитиками Условия: — Удалённая работа по РФ — Оформление по ТК РФ или ИП — Техника предоставляется — ДМС со стоматологией — Компенсация фитнеса — Скидки на обучение, кино, Skyeng — Индексация ЗП

Задачи: — Разработка и поддержка пайплайнов. — Проектирование ETL/ELT-процессов для переноса данных из PostgreSQL и других источников в ClickHouse. — Написание надёжных и идемпотентных DAG в Airflow для регулярного обновления витрин данных. — Построение слоёв данных с использованием dbt. — Обеспечение качества данных: тесты, проверка свежести, мониторинг аномалий. — Оптимизация хранилища и производительности. — Тюнинг ClickHouse: настройка схем таблиц под конкретные бизнес-запросы, устранение узких мест. — Оптимизация SQL-запросов для снижения нагрузки на БД. — Управление ресурсами кластера ClickHouse: CPU, RAM, Disk I/O. — Контроль стоимости хранения. — Администрирование и надёжность. — Обеспечение отказоустойчивости: настройка репликации и бэкапов. — Мониторинг состояния пайплайнов и баз данных. — Оперативное реагирование на инциденты. Требования: — Глубокое знание ClickHouse. — Проектирование схем: знание семейства движков MergeTree, выбор ключей партиционирования и сортировки для оптимального сжатия и скорости чтения. — Оптимизация запросов: умение читать планы запросов, оптимизировать потребление памяти, настраивать материализованные представления (Materialized Views) и проекции. — Администрирование: настройка шардирования и репликации, управление TTL, мониторинг слияний. — Инструменты ETL/ELT и оркестрация. — Оркестрация: управление сбором данных через Apache Airflow. — Трансформация: опыт работы с dbt для построения слоев данных. — Языки и инфраструктура. — Python: разработка ETL-скриптов, работа с Pandas, интеграция с API. — SQL: владение на уровне эксперта (аналитические запросы, оптимизация). — Инфраструктура: Docker (для развертывания ClickHouse), Git. Условия: — Удаленная работа из любой точки мира. — Конкурентная зарплата + performance премия 2 раза в год. — Гибкий график и фокус на результат. — Оплата обучения, курсов и конференций. — Возможность реально влиять на продукт и команду.

Ищем Asterisk / VoIP Engineer с опытом от 2 лет. Если уверенно работаете с телефонией, SIP и Linux-инфраструктурой — здесь готовы платить за реальную экспертизу. Требования: — Опыт работы с Asterisk от 2 лет; — Знание SIP, dialplan; — Опыт работы с ARI / AMI; — Знание Linux; — Опыт работы с Fail2Ban, firewall; — Опыт работы с MariaDB / MySQL; — Опыт работы с Redis, Nginx; — Опыт работы с Grafana / Prometheus. Будет плюсом: опыт с Heplify / Homer и Node.js.

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. Your job is to make sure every payout and transaction lands with the right person. We have spent years getting very good at protecting the things a marketplace has always had to protect: checkout fraud, account takeover, courier abuse. But we are no longer only a marketplace. We now issue banking products, lend to merchants, move instant payouts to couriers, and collect cash on the doorstep. Every one of those is a new way for money to leave the platform. This is a new team, and it owns that surface: fraud wherever money moves through the platform. Who receives it, who lends it, who collects it, and who holds it in a financial account. Think instant payout rails, merchant cash advances, and platform-issued banking and earned-wage products serving millions of couriers and merchants. These are live loss surfaces, and the volume grows with every financial product we launch. We are now looking for a Backend Engineer (Golang) to build that protection. You will design and ship real-time detection and automated enforcement for our financial products across DoorDash, Wolt, and Deliveroo. The work is high-throughput, low-latency, and unusually consequential: a rule you ship on Monday can stop a serious loss by Friday. It is also close to greenfield, so you will be setting the patterns every future financial product inherits on day one. This role will be based in London , UK as one of the founding engineering roles in our London hub, working closely with our teams in Helsinki and Berlin. What you'll do: Build and maintain high-throughput, low-latency backend services in Go that score financial events in real time, including payout enrollments, bank account links, credit applications, and account-to-account transfers. Design fraud detection and automated enforcement for our financial products end to end: from signal collection through to the decision that blocks a fraudulent payout. Build on and extend our shared fraud decisioning platform, so signals, rules, and models work across all three of our brands instead of being rebuilt three times. Partner closely with risk analysts, data scientists, and product managers to turn observed fraud patterns into shipped detection, and to know when a rule, a model, or a product change is the right answer. Work across team boundaries with our account security, payments fraud, and financial product teams. We build on their signals rather than rebuild them, so clean interfaces matter. Contribute to architectural discussions and technical decisions as we establish the fraud infrastructure baseline for financial products, with support from senior engineers on the team. Write well-tested, observable code and help the team hold a high quality bar. In fraud, a silent failure is a loss event. Our expectations: 3 to 6 years of professional software engineering experience, including backend services you have shipped and owned in production. 1+ years of production experience in Golang, or strong experience in another backend language and real enthusiasm for picking Go up quickly. A working understanding of low-latency, high-throughput distributed systems. Real-time decisioning comes with a latency budget, and you are keen to learn to build inside one. Hands-on experience with SQL and/or NoSQL databases, and some exposure to event-driven architectures (Kafka or similar). Willingness to operate what you build, including a share of on-call, with a pragmatic approach to reliability. Uses AI tooling in day-to-day development and can critically evaluate its output for correctness and quality. Nice to have Experience in fraud, risk, payments, lending, or financial crime, especially money movement fraud, bank account linking fraud, payout abuse, or lending fraud. Experience with rules engines, real-time feature stores, or ML model serving in a decisioning path. Background in Kotlin, Java, Python, or Node.js alongside Go. Familiarity with cloud infrastructure (AWS, GCP). Experience working across multiple brands, regions, or regulatory regimes. What we value A product-oriented mindset. You think beyond the ticket, understand the "why" behind the work, and take a high level of responsibility for outcomes rather than output. Comfort with ambiguity. This is a new team on a new surface; parts of the charter are still being drawn, and you will help draw them. A track record of owning a project or feature end to end, especially in fast-paced environments. Clear and proactive communication, with a collaborative spirit. We work across three companies and several time zones, so we move fast, but we succeed together. An adversarial instinct. The best fraud engineers enjoy thinking like the attacker. 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 .

Описание вакансии Международный fintech. Задачи: — Разрабатывать и развивать сервисы на .NET для core-функционала финтех-продукта — Проектировать API/интеграции, работать с асинхронными процессами и брокером сообщений — Повышать надежность и observability существующих сервисов — Участвовать в code review, декомпозиции, оценке и технических решениях Требования: — .NET Core от 5-ти лет опыт проектирования и разработки сервисов — Опыт работы с реляционными бд (транзакции, оптимизации запросов) — Понимание принципов ООП, основных паттернов проектирования, SOLID, KISS, DRY — Опыт работы с брокерами сообщений и основными паттернами асинхронного взаимодействия, outbox, inbox, saga — English intermediate+ Будет плюсом: — DDD — Опыт с high-load/high-availability системами, построение resiliency — full stack ReactJS