Вакансии

Эксплуатация и тюнинг СУБД: Полный контроль над состоянием, профилированием и оптимизацией PostgreSQL под конфигурацию серверов в AWS; Отказоустойчивость и HA/DR: Настройка и сопровождение репликации, Patroni, PgBouncer, бэкапирования и катастрофоустойчивости;

- Превращать телеметрию автономного транспорта в данные, удобные для анализа: разрабатывать и запускать Spark-пайплайны, продумывать преобразования и проверки качества. - Подключать новые источники данных: разрабатывать интеграции с различными системами и обеспечивать надёжную загрузку данных в хранилище.

Задачи: — Дизайн и построение LLM пайплайнов, AI агентов и RAG-систем с функциями вызова инструментов и структурированным выводом (JSON schema) — Разработка production-grade Python сервисов с использованием Django, Celery, Redis — Валидация продуктовых гипотез на основе реальных данных и аналитики — Измерение и оптимизация качества, производительности и стоимости LLM — Тесное сотрудничество с продакт-менеджерами и инженерами для превращения идей в масштабируемые решения Требования: — Опыт создания production LLM приложений — Практические знания RAG, embeddings, векторного поиска, prompt engineering и оценки LLM — Опыт работы с LangGraph, LangChain или аналогичными фреймворками — Сильный опыт Python backend (Django, PostgreSQL, асинхронное программирование) — Навыки работы с SQL и Pandas, ориентированность на данные — Владение английским языком на уровне B2-C1, русским на уровне C1 — Локация: любой город, кроме России и Беларуси Будет плюсом: — Опыт работы с векторными базами данных (Qdrant, pgvector и др.) — Опыт дообучения, классификации текста или работы с embedding моделями — Опыт с Kubernetes, gRPC или Go Условия: — Удалённая работа — Гибкий график — Профессиональное развитие Компания Mad Devs занимается решением сложных задач и созданием инновационных решений в области AI, проекты охватывают Европу, США и Юго-Восточную Азию. Вакансия направлена на революцию в юридической индустрии с помощью AI.

In this role, you will work on the development and continuous improvement of Sophea AI, expanding our LLM capabilities across European languages, with a particular focus on Polish. You will be deeply involved in LLM pre-training, training from scratch, fine-tuning, model evaluation, inference optimization, and production-grade ML systems.

-Разрабатывать автоматизированные тесты для веб-сервиса (функциональные тесты api/ui, визуальное тестирование, нагрузочное тестирование). -Поддерживать автотесты (6000+ api, 600+ ui).

Чем предстоит заниматься: — Развивать Kubernetes-инфраструктуру в облаке и на bare-metal.

Location: London, United Kingdom - Deliveroo 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. Senior Software Engineer, GenAI Platform About the Team Deliveroo's GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalisation to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at Deliveroo and DoorDash, leading the design and architecture of our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high-impact systems and pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. You’re excited about this opportunity because you will… Lead the design of infrastructure that helps teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Own and evolve our open-weights serving stack — real-time GPU endpoints, high-throughput batch inference, and fine-tuning (SFT/DPO/LoRA) — alongside the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. Architect scalable, high-performance systems for model serving, batch inference, GPU autoscaling, and fine-tuning that power real customer and internal automation use cases Push the cost and latency frontier of GPU inference — turning batch jobs that took days into hours and cutting inference cost by multiples — while giving product teams a clean choice across open-weight and closed-source models with reliability, fallback, observability, and cost controls built in. Build platforms that support rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence. Partner closely with — and raise the technical bar for — ML engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and Deliveroo to turn emerging GenAI capabilities into durable platform primitives. Set technical direction for the future of the company's centralised GenAI platform — including emerging directions such as reinforcement learning (RLHF/RLVR), agent optimisation, and other post-training and agentic techniques — enabling the next generation of AI-powered products, agents, automation, and personalisation. We’re excited about you because… BSc, MSc or PhD in Computer Science or equivalent 5+ years of industry experience in software engineering Deep backend engineering fundamentals, especially in Python and distributed systems. Track record of designing and owning production services, APIs, data pipelines, or ML infrastructure at scale. Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization. Deep hands-on experience with LLM inference and/or fine-tuning of open-weight models in production — serving (latency, throughput, batching, autoscaling, GPU utilization) and/or fine-tuning (SFT/DPO/LoRA). Demonstrated technical leadership: leading design across ambiguous, fast-moving technical areas, mentoring engineers, and turning customer use cases into reusable platform capabilities Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Nice To Haves Experience with LLM inference engines and serving frameworks (e.g., vLLM, SGLang, TensorRT-LLM) in production Experience with distributed/multi-node fine-tuning and training pipelines (SFT, DPO/RLHF, LoRA), including data preparation and evaluation GPU performance work — multi-node/distributed inference, KV-cache/memory optimisation, quantisation (FP8/INT8/AWQ/GPTQ), or cold-start/throughput tuning Experience with Kubernetes, cloud infrastructure (AWS/GCP), GPUs, serverless/elastic GPU platforms (e.g., Modal), or high-throughput batch systems Experience with LLM gateways, model routing, vendor abstraction, or cost attribution Experience building developer platforms, internal platforms, or self-serve infrastructure Experience building and deploying AI agents or MCP servers in production Experience with eval systems, LLM observability, tracing, RAG, search, or vector databases 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 .

Основной фокус роли — связка native-платформ iOS/Android с Flutter: работа с native APIs, embedders и platform adaptation code, то есть скорее глубокая работа на стороне iOS/Android и интеграции этих компонентов с Flutter.

You will be working day to day on AWS, our infrastructure-as-code, our CI/CD setup, observability, and the on-call rotation. A meaningful part of the work is automation: when we find ourselves doing the same thing twice, we usually invest in tooling rather than writing another runbook.

Looking for a strong Lead QA Engineer to take ownership of QA for a manufacturing management platform, with the current focus on a production line scheduling application.

– Разрабатывать и сопровождать потоковые приложения на Apache Flink: подключать новые домены и типы событий, реализовывать дедупликацию, идемпотентную обработку, обогащение через Redis и маршрутизацию невалидных событий в DLQ; участвовать в восстановлении и дозагрузке данных;

Задачи • Проверять корректность финансовых расчётов: создавать эталонные сценарии, рассчитывать результат вручную и сверять его с движком. • Разрабатывать тесты-инварианты — проверять свойства, которые должны выполняться на любых данных.

💎 Разработка и поддержка backend-сервисов в микросервисной архитектуре для системы защиты от мошенничества: обработка транзакций в реальном времени, ответственность за производительность, мониторинг и разбор инцидентов, работа с инженерами, продактами и дизайнерами.

Location: Paris, Remote Workplace: remote Our Security and IT team keeps the 360Learning platform secure, compliant and auditable for the 1,500 organisations that learn on it every day. As a Senior DevSecOps Engineer, your mission is to make our infrastructure secure by design, detectable by default, and provable at audit time. 360Learning runs its learning platform on Azure and Kubernetes, certified ISO 27001:2022 and SOC 2 Type II. Over the past two years the technical security workload has grown on every front: a larger and more regulated customer base sending their own scans and security assessments, a wider detection and response scope, more infrastructure to keep hardened and auditable, and a growing backlog of security engineering projects that never reach the top of the queue. We are creating this position to add real technical capacity on the infrastructure side of security, and to move part of our security posture from manual effort to automated guardrails. You will be the bridge between security and platform engineering: deep enough in infrastructure to fix things yourself, and close enough to security operations to know what to look for. “Ours is a small, senior team with a broad scope: information security, compliance, infrastructure governance and internal tooling, with dual audit accountability on ISO 27001:2022 and SOC 2 Type II. That means direct impact and no layers between you and the decision. Roughly half of this role is greenfield build work you will own end to end.” Guillaume Seigneuret, CISO and Hiring Coach. Within 1 month, you will: Complete our onboarding and learn how we work through our own platform and our Convexity culture Map our Azure and AKS environment, our detection and logging coverage, and our ISO 27001 and SOC 2 control scope with the CISO and the Security Engineer Meet the DevOps, platform engineering and IT teams you will work with daily Shadow alert triage and one customer security assessment end to end Within 3 months, you will: Be autonomous on our AKS and Azure environment and handle infrastructure related alerts end to end Have shipped at least one concrete hardening or automation improvement in production Own the infrastructure scope of vulnerability management, from triage to remediation follow up Within 6 months, you will: Have the honeypot live and producing high fidelity alerts Have measurably widened SIEM connector coverage, with documented log sources and retention Run infrastructure vulnerability remediation on a predictable cycle with SLA reporting Within 12 months, you will: Manage detection content as code, with reviewed and tested rules and documented runbooks Have largely automated audit evidence on the infrastructure scope Have eliminated long lived credentials on the critical paths, so engineering teams ship on secure defaults they did not have to think about The Skill Set: 5+ years in infrastructure, cloud or platform engineering with a strong security focus, or in security engineering with hands on infrastructure practice Production experience with Kubernetes: RBAC, network policies, admission controllers, secrets handling, workload identity, runtime security Solid cloud experience, ideally Azure. Strong AWS or Google Cloud experience with a genuine interest in converting works too Infrastructure as code: Terraform, GitOps workflows, CI/CD pipelines Scripting and automation: Python or Go, plus shell. Comfortable reading and writing code, and opening pull requests on repositories owned by other teams Log analysis and investigation: cloud audit logs, query languages, correlation across identity, network and application sources Fluent English (US/UK) / B2 level or equivalent (FR). Enthusiasm for our working environment explained here: https://bit.ly/Convexity360L What we offer: Compensation: Package includes base salary, a variable component and equity 📈 Benefits/Perks : Work From Home stipend, RTT, lunch vouchers, medical insurance, gym subscription, 1 month parental leave for the second parent. Balance: Flexible hours, full remote work possible anywhere in France 🏠 Diversity, Equity, and Inclusion : We have 6 active ERGs including Mental Health, Environmental/Sustainability, Women, Parents, LGBTQIA2S+, and Ethnic Diversity. Each group has at least one executive team member serving as a member of the group, bringing greater awareness to each group’s activities and providing a quick path to impact 🤝 Corporate Social Responsibility : Review our CSR Charter: 360learning.com/blog/corporate-social-responsibility-charter 🌎🌏🌍 Culture: A framework that will help you make an impact - envision our way of working and our Convexity Culture: https://bit.ly/Convexity360L & find out more about the teams, product and processes https://bit.ly/42H1ggC 🚀👩🏻‍💻🏆 Interview Process: Phone Screen with our Talent Acquisition Manager Discovery Meeting with our Head of Security Live exercise with our Head of Security and our Head of Devops: investigation of an incident scenario, or review of an insecure infrastructure configuration Clarification Meeting with the Security Engineer and a DevOps engineer Culture Fit Meeting with our VP of Engineering Offer! Who We Are 360Learning enables companies to upskill from within by turning their experts into champions for employee, customer, and partner growth. With our LMS for collaborative learning, Learning & Development teams can accelerate upskilling with the help of internal experts instead of slow top-down training. 360Learning is the easiest way to onboard and upskill employees, train customer-facing teams, and enable customers and partners–all from one place. 360Learning powers the future of work at 1,700 organizations. Founded in 2013, 360Learning has raised $240 million with 400+ team members across North America and EMEA. Learning Includes Everyone. In concert with our culture, 360Learning believes learning includes everyone and that means embracing the strengths of diversity, connectedness, and inclusion. Through conscientious efforts, our global footprint celebrates cultures, perspectives, and experiences from all over the world to support our platform that is built for all regardless of race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. Thus, 360Learning is proud to be an equal opportunity workplace, and we commit to continue this throughout our processes for recruitment, compensation, benefits, performance, promotion, and all other conditions and terms of employment. We want to learn from and with you!

Ищем Fullstack QA Engineer (Middle+) в крупный FinTech-проект. • QA от 3 лет;

What you will own. Take product ideas from problem definition through design, implementation, rollout, and iteration, including experiments that may grow into standalone products.

Location: Australia Workplace: Remote ABOUT THE TEAM The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them — together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists. WHAT YOU WILL DO - Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform. - API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services. - Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools. - Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation. - Oncall: Participate in the daytime oncall rotation along with the rest of the team. - UI/UX Implementation: Build responsive, intuitive user interfaces that make complex AI functionalities accessible and valuable to users of all technical backgrounds. WHAT YOU WILL BRING ALONG - 5+ years of software engineering experience in production environments - Exposure to working directly with AI/ML technologies - A high level of ownership and can drive features from concept to production with minimal supervision - Ability to thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders - Strong frontend skills with TypeScript/JavaScript and React Nice to have - Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases - Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment - Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus - Experience building data-oriented interfaces and visualizations PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new team member who joins our company receives stock options. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Предстоит: Разработка и улучшение пайплайна LLM post-training: SFT, preference optimization, Offline / Online RL;