Вакансии

Location: Munich; Warsaw; London Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE The Inference Foundation team owns the core of Mistral's inference stack: the inference engine and its orchestration, from the feature set and configuration that serve our models in production to the release machinery that keeps the stack current and production-grade. This is a hybrid position spanning production LLM serving, engine and platform development, and capacity engineering. You will work on three intertwined problems: 1. Optimize the inference stack at scale — feature development and fixes in the engine and orchestrator, squeezing more throughput and lower latency out of every GPU under strict quality-of-service targets. 2. Make capacity elastic — scaling up and down should be cheap and fast, not a performance cliff. 3. Power the training of our frontier models — high-performance serving that keeps RL and post-training loops running at full speed.   What You Will Do INFERENCE ENGINE & ORCHESTRATION - Develop and fix the core of the inference stack — engine and orchestrator — including feature selection, configuration, and tuning for maximum performance at scale - Own the release process for the serving stack: validated, regression-free releases through automated performance gates and progressive rollout - Drive improvements and fixes upstream when the open-source engine is the right place for them PERFORMANCE & CAPACITY AT SCALE - Optimize serving efficiency across the fleet — driving down pod startup time, tackling cold-cache regressions on scale-up, smarter caching and offloading - Optimize and maintain the optimal serving topology — overlap communication and transfers with computation, ensure optimal placement, connectivity, and routing SERVING FOR FRONTIER TRAINING - Build the serving infrastructure that powers RL and post-training for our frontier models - Optimize inference performance across the full spectrum of our workloads   What We're Looking For - Experience building and running ML/LLM services at scale, with clear latency and availability targets - Hands-on experience with inference engines such as vLLM, SGLang, TensorRT-LLM, or others - A solid grasp of inference internals: prefill vs. decode, KV-cache behavior, batching, scheduling, speculative decoding, parallelism strategies - Familiarity with distributed and disaggregated serving architectures - Comfortable debugging across the full stack — CUDA/NCCL, kernels, containers, networking, storage - Python for systems tooling and backend services; PyTorch - Kubernetes for running infrastructure at scale - GPU and networking fundamentals: CUDA runtime, NCCL, InfiniBand/RDMA It Would Be Great If You Have - Demonstrated vLLM/sglang know-how — upstream contributions, or a track record of running in demanding production environments - Hardware-aware optimization for various model architectures - Experience serving MoE models at scale (expert parallelism, expert placement/load balancing) - CUDA/Triton kernel development; Nsight Systems/Compute profiling - Rust and/or C++ in production systems WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: United States (Remote); Boston, Massachusetts; Los Angeles, California; Raleigh, North Carolina; Denver, Colorado; Seattle, Washington; New York, New York; San Francisco, California; Portland, Oregon Workplace: Remote ROLE SUMMARY Temporal customers are building some of the most critical, reliability-sensitive systems in production. They choose Temporal to move faster, ship with confidence, and operate durable workflows at scale. As a Senior Professional Services Engineer, you will help customers and partners move from design to production-ready execution quickly and safely. You will establish strong delivery patterns, operational standards, and enablement that scale across teams and environments (cloud and self-hosted). This is a delivery-focused role centered on making systems work in the real world, and leaving customers better equipped than when you arrived. WHAT YOU’LL DO - Deliver production-ready Temporal implementations by co-building initial workflows with customer and partner engineering teams - Implement and teach production-safe workflow patterns, including retries, timeouts, heartbeats, determinism, and versioning - Identify and remove early activation blockers before they become escalations - Help customers stand up and operate Temporal Server in production, including self-hosted environments - Define worker deployment, scaling, and operational guardrails, including upgrade strategy, failure handling, and capacity planning - Establish observability and reliability standards by defining metrics, alerts, and dashboards for workflows, workers, and Temporal Server - Create repeatable runbooks, templates, examples, and documentation that improve delivery quality across engagements - Lead hands-on workshops and training that enable customer and partner engineers to operate safely and independently - Own complex technical delivery issues end-to-end, partnering with Support and Platform Architects to reduce escalations to Engineering - Provide actionable product and engineering feedback based on real-world implementation patterns and failure modes WHAT YOU’LL BRING - Experience delivering and operating production systems where reliability and incident response matter - Strong understanding of distributed systems, failure modes, scaling tradeoffs, and operational safety - Hands-on coding ability in at least one major language such as Go, Java, Python, or TypeScript - Experience deploying and operating production services in cloud and or self-hosted environments - Ability to design and communicate operational standards, including on-call readiness, runbooks, and capacity planning - Comfort working directly with customers in high-stakes delivery moments, with a calm and credible approach - Strong debugging skills and ability to navigate ambiguity and messy real-world constraints - Ability to teach and enable other engineers, not just deliver the work directly NICE TO HAVE - Experience with workflow orchestration systems, distributed task processing, or durable execution concepts - A track record of building observability programs, including dashboards, alerting strategies, and operational maturity models - Proven ability to create reusable reference architectures, templates, or internal enablement programs - Strong partnership skills to collaborate with product and engineering teams and translate field learnings into roadmap improvements - Background in working with partners or services delivery models at scale Temporal Technologies is an Equal Opportunity Employer. Temporal Technologies does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need. We embrace and celebrate differences and diversity. Temporal is committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. If you need to request a reasonable accommodation, please let your Recruiter know so we can assist.

Location: AU: Melbourne: (260 Burwood Rd); AU: Sydney (45 Clarence St) Workplace: Hybrid The role As our 'Engineering Manager - Data', you will lead the engineering team responsible for creating and maintaining core models on our data platform. In this role, you will balance strategic leadership with technical delivery, shaping platform architecture while staying close enough to execution to ensure delivery, stability, and quality standards are met. You will empower and grow senior engineering talent, establish operational standards, and manage risk and dependencies across key quarterly initiatives. Partnering closely with product, platform, and security teams, you will ensure high-quality, scalable data products are delivered to solve meaningful customer problems. The team & how they connect The 'Dataverse' team consists of nine engineers located across Australia, New Zealand, and Canada who build and maintain the core models in our data platform. Working across remote locations, the team collaborates closely to manage cross-team dependencies and maintain continuous alignment. They foster an environment grounded in knowledge sharing, constructive feedback, and empathy for stakeholders. Initially, the role may focus on - Designing and building core models on the data platform using AWS and Snowflake infrastructure. - Streamlining real-time data flows and streaming architecture across platform services. - Leading delivery execution for complex data platform initiatives while managing dependencies and risks. - Coaching senior engineers, elevating engineering standards, and supporting team adoption of DataOps practices. Where and how you can work This role offers flexible hybrid working arrangements based out of our Sydney or Melbourne offices. You can balance remote work with designated office boost days to connect, whiteboard, and collaborate in person with your team. Here are some of the things we're looking for, for this role: - A background in data platform delivery alongside data engineering expertise and data modelling capability. - Practical familiarity with cloud infrastructure like AWS and Snowflake, along with an understanding of real-time streaming technologies and data flows. - Your leadership style combines delivery focus with the technical breadth required to guide architectural decisions and step in hands-on when required. - Proven capability in coaching senior engineers, setting clear expectations, and supporting individual career progression. - Demonstrated proficiency managing platform health, establishing Service Level Objectives, and leading operational performance. - Strong collaborative skills to build trusted relationships across product, platform, and security teams. Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

Задачи: — Разрабатывать, обучать и внедрять ML/DL-модели для бизнес-задач. — Строить AI-агентов и multi-agent workflows с tool/function calling, MCP и LangGraph/LangChain (или аналогами). — Проектировать RAG-системы: эмбеддинги, hybrid search, reranking и векторные БД. — Выполнять fine-tuning LLM, оптимизировать inference и интегрировать модели через API и микросервисы. — Участвовать в MLOps/LLMOps: evaluation, мониторинг, tracing, guardrails и повышение качества AI-систем. Требования: — Опыт: от 2 лет в ML/DL или разработке AI-систем. — Стек: Python, NumPy/pandas, scikit-learn, PyTorch / TensorFlow, Hugging Face Transformers. — Знания: понимание ML/DL, архитектуры трансформеров и принципов работы LLM. — Навыки: практический опыт с AI-агентами, RAG, vector DB и structured output; уверенный Git и деплой в production. — Языки: знание узбекского и английского (Intermediate+) языков. Будет преимуществом: — Разработка API на FastAPI / Django REST Framework и контейнеризация с Docker. — Computer Vision и видеоаналитика (OpenCV, YOLO, tracking, RTSP). — MLOps/LLMOps-инструменты, self-hosted inference, GPU и Kubernetes. — Мультимодальные модели или голосовые пайплайны (STT-LLM-TTS). Условия: — Развитие: оплачиваемые профильные курсы, IT-конференции, фестивали и тимбилдинги. — Условия: бесплатные вкусные обеды в офисе. — Карьера: реальные масштабные задачи, влияние на продукты компании, профессиональный и финансовый рост. — Локация: офис в г. Ташкент. — График: 5/2, с 09:00 до 18:00. — Командировки: в г. Коканд (организуются и оплачиваются компанией). — Зарплата: От 14.000.000 сум.

Location: Europe Workplace: Remote ABOUT ENEBA At Eneba, we’re building an open, safe and sustainable marketplace for the gamers of today and tomorrow. Our marketplace supports close to 20m+ active users (and growing fast!), provides a level of trust, safety and market accessibility unparalleled to none. We’re proud of what we’ve accomplished in such a short time and look forward to sharing this journey with you. Join us as we continue to scale, diversify our portfolio, and grow with the evolving community of gamers. ABOUT THE ROLE We’re looking for an Analytics Engineering Lead to set the direction for analytics engineering at Eneba and help the team deliver trusted, business-ready data. You’ll lead a team of around 10 analytics engineers. You’ll define what analytics engineering owns and where it is going, connect the team’s work to real business needs, and ensure curated data can be used directly by business teams, BI tools, and AI agents without an analyst in between. WHAT YOU’LL DO - Create and own the analytics engineering strategy, direction, and goals. - Lead, coach, and develop a team of around 10 analytics engineers through regular feedback, one-to-ones, performance management, review cycles, and hiring, helping them become increasingly autonomous. - Establish the analytics data-modeling architecture, engineering principles, quality standards, and ways of working that guide how the team builds and maintains models. - Ensure analytics engineering work begins with a clear understanding of the business problem and delivers data that people can use with confidence. - Enable reliable self-service analytics by making curated data usable by business teams, BI tools, and AI agents, with appropriate semantic layers, metrics, discoverability, and governance. - Evaluate the current analytics landscape and make pragmatic, evidence-based decisions about what should be improved, stopped, rebuilt, or delegated. - Partner directly with stakeholders across the company, including teams such as Accounting, Payments, and Marketing, as well as senior leaders. - Build a strong understanding of Eneba’s business and translate varied stakeholder needs into a clear direction for the team. - Identify and empower technical experts within the existing team to help define and implement engineering standards. - Evaluate analytics tooling and delegate technical discovery where appropriate, while retaining final ownership of analytics engineering architecture and tooling decisions. REQUIREMENTS - Proven experience leading and developing data, analytics, or analytics engineering and people-management in product-focused tech companies. - Experience defining strategy and setting direction for analytics engineering, data modeling, or a closely related function. - A track record of establishing data-modeling architecture, principles, or standards that guide how other engineers build and maintain models. - Strong business judgment: you focus on why data is needed and what problem it solves, not only how models are built. - Strong stakeholder management and communication skills, with proven experience partnering closely with product leadership and representing data in executive-level and cross-functional discussions. - Ability to form clear, evidence-based opinions, challenge existing approaches, and lead change under sustained pressure including recommending that work be stopped or rebuilt when needed. - Experience operating in a high-growth, fast-moving organization with low approval layers, where data supports many business functions. Scale-up experience is helpful. - Working knowledge of SQL and data modeling, hands-on experience with DBT, and familiarity with at least one BI or dashboarding tool. - Fluent English (business proficiency required) What it’s like to work at Eneba - Opportunity to join our Employee Stock Options program. - Opportunity to help scale a unique product. - Various bonus systems: performance-based, referral, additional paid leave, personal learning budget. - Paid volunteering opportunities. - Work location of your choice: office, remote, opportunity to work and travel. - Personal and professional growth at an exponential rate supported by well-defined feedback and promotion processes. - We’re an international team and our business language of choice is English. Good English level is required, proficiency is preferred. Please submit your resume in English - To find out about how we handle your personal data, make sure to check out our Candidate Privacy Notice https://www.eneba.com/candidate-privacy-notice   #LI-LK1

Задачи: — 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 — Развивать архитектуру Data Lake / DWH — Вместе с командой формировать общие подходы к разработке, мониторингу и сопровождению пайплайнов Требования: — Практический опыт разработки и сопровождения пайплайнов данных — Опыт работы с PySpark, Python и SQL — Опыт работы с Data Lake / DWH и понимание принципов построения ETL/ELT-процессов — Понимание принципов распределённой обработки данных Будет плюсом: — Опыт работы с Trino+S3 — Опыт оркестрации пайплайнов с помощью Airflow — Знакомство с Data Vault 2.0 — Знание Scala и опыт её использования для обработки данных — Опыт развития платформы данных на ранних этапах: от выбора решений до их внедрения и сопровождения

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.

Задачи: — Развивать Kubernetes-инфраструктуру в облаке и на bare-metal. — Автоматизировать инфраструктуру с помощью Terraform и Ansible. — Создавать и улучшать GitLab CI-пайплайны, работать с Helm и ArgoCD. — Развивать мониторинг, логирование и алертинг, участвовать в решении инцидентов. — Писать инструменты и автоматизацию на Python или Go. — Помогать командам разработки работать с платформой. Требования: — Практический коммерческий опыт в DevOps или инфраструктурной инженерии. — Уверенная работа с Linux и понимание сетей. — Опыт Kubernetes или OpenShift. — Практика автоматизации инфраструктуры и настройки CI/CD. — Опыт работы с мониторингом и логами. — Умение рассказать о своих решениях и личном вкладе в проекты. Условия: — Удалённая работа и гибкое планирование рабочего времени с учётом командного покрытия и поддержки. — 20 оплачиваемых дней отпуска + 12 дополнительных дней отдыха в год. — Больничные со 100% оплатой. — Поддержку профессионального развития: курсы, сертификации и обучение. — Развитие в направлении Platform Engineering и SRE с поддержкой технического лида.

Location: Warsaw We're looking for a Senior Infrastructure Engineer who brings strong software engineering skills and a deep understanding of production systems. This role is a good fit for someone who enjoys building systems that make infrastructure more scalable, reliable, and easy to operate – using code, not runbooks. You'll work with a highly collaborative team to design and build the internal platforms that power all of Asana, from product features to AI systems to offline analytics. Our tech stack includes: AWS, Kubernetes (EKS), MySQL (RDS), OpenSearch, DynamoDB, Redis, Terraform, Datadog, TypeScript, Scala, Go, and Python. We’re especially interested in people who think like backend engineers but care deeply about systems – things like failure modes, operational cost, debuggability, and performance. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements. We offer a Contract of Employment (UoP) for our employees in Poland. What you’ll achieve: Design and build frameworks, tools, and services that improve the reliability, observability, and scalability of Asana’s infrastructure. Lead end-to-end projects, from scoping and design through to rollout, across multiple systems and teams. Improve the operability of stateful infrastructure like MySQL, OpenSearch, and DynamoDB – and help drive Asana’s long-term vision for storage reliability. Debug production issues across the stack. Yes, there’s an on-call rotation – but this isn’t a pager monkey role. You’re here to fix things properly and make sure they don’t break again. Partner with product teams to shape a service-oriented architecture that enables fast, reliable development. Share knowledge through code reviews, design discussions, and mentorship. About you: Strong software engineering background – you’re comfortable writing production code and designing systems (we use Go, Python, Scala, TypeScript). 5+ years of experience building and operating backend systems at scale. Familiarity with distributed systems and storage technologies (SQL, NoSQL, Search), especially in cloud environments. Experience with AWS services (e.g. RDS, EKS, IAM), Terraform, and monitoring tooling like Datadog or similar. Solid understanding of SRE principles (e.g. SLIs/SLOs, error budgets, incident response), but you approach reliability as a software problem first. Clear communicator and strong collaborator – you're comfortable navigating trade-offs with stakeholders across the stack. Important: If you’re only comfortable with scripting, this isn’t the right role . We’re looking for engineers who build and ship real systems. Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making Why this role? Founding team: You’ll be one of the first SREs in Warsaw – and a key player in a growing team. Drive real change: This isn’t a role where you’ll just patch up legacy systems. We are expecting (and supporting) real architectural changes to improve reliability, scalability, and long-term operability. Big impact: Our product is scaling fast, and reliability is a top company priority. Room to grow: As this team grows, so will your influence – whether you want to lead projects, mentor others, or help shape how we scale. Global collaboration : Work closely with experienced engineers in San Francisco, Reykjavik, and Warsaw, while helping build the future of SRE at Asana. What we'll offer: Generous, transparent and fair compensation system (base salary and generous Restricted Stock Unit for Asana Inc.). Contract of Employment ( with 50% tax deductible costs for author’s rights usage for Engineers). Health insurance with dental and travel coverage (Lux Med). Lunch catering on the days that you work from the office. Career growth budget. Home office setup budget. Gym/Fitness reimbursement. Fertility healthcare and family-forming support with Carrot . Mental health support in Modern Health. Group life insurance. MacBooks with all necessary accessories. For this role, the estimated base salary range is between 31,000 - 36,000 PLN gross monthly on the contract of employment (UoP). The actual base salary will vary based on various factors and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base compensation range for this role may be modified. Our total compensation consists of base salary and equity (RSUs). #LI-Hybrid #LI-AZ About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to 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 law. Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

Location: Almaty, Kazakhstan; Warszawa, Poland; Tbilisi, Georgia; Belgrade, Serbia; Yerevan, Armenia; Vilnius, Lithuania; Madrid, Spain; Lisboa, Portugal; Sofia, Bulgaria; Larnaca, Cyprus; Bucharest, Romania Workplace: fully We are looking for a Senior Analytics Engineer: 🗣 Language Proficiency: Intermediate 🧾 Employment type: Full time 🌍 Candidate Location: EU, Serbia, Georgia, Armenia, Kazakhstan 🕐 Working Time Zone: CET 🚀 Start: ASAP 🧭 Planned Work Duration: 6 months 👥 Customer Description: The customer is a global mobility and urban services platform offering transportation, delivery, and on-demand services. 🧩 Project Description: Data delivery and attribution pipeline migration to a core data warehouse platform. ⚙️ Project Phase: Ongoing 💡 Hard Skills / Must Have: • 3+ years of Analytics Engineering, DWH Engineering, or Data Analysis experience • Expert SQL and good Python knowledge for ETL and data processing • DWH architecture, ODS, data marts, incremental loads, history handling, and deduplication • BigQuery or similar columnar databases; data mart design and optimisation • dbt for large incremental projects and Airflow or similar orchestration tools • Pipeline migration, data parity validation, Git, Data Quality, and Data Governance • Ability to translate stakeholder needs into data requirements ✨ Hard Skills / Nice to Have: • Mobile or marketing attribution data, ad network cost data, SKAN/ATT, and ad fraud data • Google Cloud Platform, Cloud Storage, and Dataform • Lightdash, Looker, or Tableau 📌 Responsibilities and Tasks: • Clarify requirements and implement changes to attribution logic, sources, and data marts • Lead migration of dbt models, Airflow DAGs, and sources to the core DWH platform • Build and optimise incremental BigQuery data marts, including recalculations and backfills • Implement data quality checks and investigate discrepancies • Analyse external inputs and ensure reliable data delivery • Participate in testing, validation, releases, and technical documentation Technology Stack: SQL, Python, BigQuery, dbt, Airflow, Git, Data Warehousing, Data Modeling, ETL/ELT, Data Quality, Data Governance Interview stages : English check (15 minutes) internal technical interview (1-1,5 hour) client interview (1 hour) client interview – cultural fit (45 minutes) What we offer Model: B2B contract with Bonapolia - one contract, one monthly invoice Rate: negotiated per candidate seniority and client budget Payment: monthly invoice, paid on the same schedule the client pays us (usually 30 days) Contract written under your country's law We handle the client-side paperwork: MSA, NDA, invoicing 🏢 About Bonapolia Bonapolia is a family-owned IT staff augmentation team based in Lisbon. We build engineering teams for product companies and IT consultancies across Europe and the US. More at bonapolia.com 📩 Ready to Join? We look forward to receiving your application and welcoming you to our team!

Задачи: — 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; — Обеспечивать полноту и качество потоков: контролировать lag, пропуски, дубли, объёмы, freshness, расхождения между источником и целевым хранилищем; участвовать в восстановлении и дозагрузке данных; — Развивать batch-пайплайны в Apache Airflow: регуляторные выгрузки день в день, bulk-загрузки в Cassandra, проверки полноты, свежести и результатов загрузки; — Подключать новые источники: разбираться в семантике событий, идентификаторах, ключах партиционирования, формате данных, ретенции, владельцах и ограничениях источника; — Cassandra, документация потоков, runbook и постмортемы; — Участвовать в on-call по понятному регламенту: локализовать инциденты, корректно эскалировать, объяснять простои и фиксировать пробелы в сборе данных. Требования: — 2–4 года опыта в Data Engineering либо backend-разработке с практическим переходом в data-направление; — Уверенный SQL и понимание работы с большими объёмами: партиционирование, шардирование, распределённые вычисления, оценка стоимости запросов и поиск узких мест; — Построение корпоративных DWH , понимание слоев данных; — Практический Kafka-опыт: producer/consumer, consumer groups, ключи и партиционирование, offsets, ретенция, replay, обработка ошибок, DLQ; — Python для data-задач и Airflow: умение разрабатывать и сопровождать DAG-и, писать идемпотентные задачи, организовывать retries и backfill; — Опыт работы с Java-кодом Flink (Python Flink может быть релевантным как опыт): читать, дорабатывать, отлаживать, разбираться в причинах рестартов, checkpointing и backpressure; — Опыт самостоятельной разработки stateful Flink-пайплайнов будет преимуществом; — Практический опыт хотя бы с одной технологией: Cassandra или ClickHouse; — Для Cassandra: понимание моделирования от паттернов доступа, partition key, TTL, консистентности и особенностей записи; — Для ClickHouse: оптимизация запросов, работа с кластером и шардами, моделирование таблиц, TTL и особенности upsert/merge-семантики; — Опыт сопровождения Airflow-пайплайнов в production; — Привычка к инженерному циклу: тесты, CI/CD, кволитигейт, мониторинг, алерты, анализ причин инцидента и профилактические действия; — Внимательность к SLA и регуляторным ограничениям: если данные нельзя терять, система должна уметь это обнаружить, объяснить и восстановить.

Задачи: — Разработка и улучшение пайплайна LLM post-training: SFT, preference optimization, Offline / Online RL; — Улучшение instruction following и построение системы benchmarking / evaluation; — Обучение LoRA / QLoRA-адаптеров под различные домены и задачи; — Работа с reward models / verifiers и reward functions для RL.

Задачи: — Ускорять и масштабировать LLM в продакшене: оптимизация инференса очень больших моделей (до 1T+ параметров), SGLang, KV/prefix caching, speculative decoding, квантизация. — Разворачивать распределенный инференс: MoE, tensor/expert/pipeline parallelism на multi-node / multi-GPU кластерах (32x H200 + AWS). — Заниматься Post-Training: обучать и дообучать модели компаньонов (SFT, DPO/RLHF), улучшать агентные каркасы и алгоритмы чата. — Осуществлять техлидство (без бюрократии и PM): ревью экспериментов команды NLP/CV (7 инженеров), выбор направлений и оценка гипотез. Требования: — Глубокий опыт оптимизации LLM в продакшене (SGLang, vLLM или TensorRT-LLM). — Опыт распределенного инференса/обучения гигантских моделей (MoE, multi-node clusters). — Понимание профилирования GPU, работы attention-кернелов и KV-cache. — Практика дообучения моделей (RLHF, DPO или аналоги). — Сильный бэкграунд на PyTorch / Transformers. — Английский или русский язык на профессиональном уровне. Плюсом будет: — Опыт разработки CUDA / Triton кернелов. — Бэкграунд в CV (опыт ускорения инференса гигантских GenAI моделей). — Опыт работы в AI-стартапах (Character.ai, Replika, OpenAI и др.) или BigTech (Яндекс, Сбер, T-Bank, Nebius, Meta, Mistral). — Профильное математическое / CS образование (МГУ, МФТИ, ВШЭ, Бауманка или топовые зарубежные вузы). Условия: — Полный Remote и максимум свободы без корпоративного gatekeeping. — Скорость: идеи становятся live-экспериментами за дни, а не quarters. — 28 дней отпуска + 7 wellness-дней в год без больничных листов. — $1,000 на обустройство хоум-офиса раз в 3 года. — Софинансирование обучения, конференций (50%) и медицинских расходов (до $1,000/год). — Доступ к опциональной A-team программе (опционы / % от выручки) после 1 года работы.

Задачи: — Проводить исследования на основе большого количества реальных гитарных джемов — Работать с существующими open source моделями и трансформировать их под музыкальные задачи — Вести полный цикл от идеи и исследования до реализации и деплоя — Заниматься и генерацией, и распознаванием игры на музыкальных инструментах — Тестировать результат сам — садиться с гитарой и проверять на слух — Строить и поддерживать инфраструктуру (Docker, облака, MLOps) Требования: — Играет на гитаре и любит музыку — Имеет опыт в audio/speech ML — генерация, распознавание, обработка звука — Готов вести полный цикл — исследования, реализация, деплой, инфраструктура (Docker, облака, MLOps)

Location: AU: Sydney (45 Clarence St) Workplace: Hybrid ENGINEERING MANAGER - APPLIED AI THE ROLE AND ITS IMPACT You will lead and grow the Internal AI Accelerator team as it expands from its current core to a fully formed engineering squad. You will own the strategy, delivery, and roadmap for how Xero designs and delivers agentic AI workflows that eliminate manual toil, speed up decision-making, and generate measurable productivity gains. This means working directly with business leaders across G&A, Finance, P&C, and IT functions to co-build reusable AI patterns and governance frameworks that last. You will shape how Xero thinks about AI delivery long after your tenure, building playbooks and reference architectures that other teams can pick up and run with. What your engineers build goes into production and real people rely on it. One month you are partnering with finance, the next you are embedded in IT. You set the pace, you unblock the path, and you hold your team accountable to shipping. THE TEAM AND HOW THEY CONNECT The Internal AI Accelerator team is a small, high-impact crew of engineers embedded across Xero's business units. They partner directly with product, engineering, and business teams to design and ship AI workflows in weeks, not months. The team operates with a direct line to senior stakeholders and a genuine mandate to move fast. Together, you are genuinely curious about what works and what doesn't, learning openly from every project and sharing what you discover. THE TEAM IS CURRENTLY WORKING ON The team is expanding from a proof-of-concept phase into building at scale. You will focus on growing the engineering capability across multiple workstreams. Initially, your priorities will be: - Scaling agentic AI delivery across multiple business domains (finance, HR, support, operations) - Building reusable patterns, platforms, and governance frameworks that other teams can adopt - Designing and implementing the technical architecture for enterprise AI deployments - Establishing best practices for AI safety, evaluation, and operations at scale WHERE AND HOW YOU CAN WORK This role is based in Sydney. You will work in a hybrid model with core collaboration days in the office. Xero supports flexible ways of working, and regular "boost days" bring our ANZ teams together for connection and planning. HERE ARE SOME OF THE THINGS WE ARE LOOKING FOR - You bring solid engineering credibility, ideally from shipping production software at scale, so you can make sound technical decisions and earn your team's respect without needing to code day-to-day. - Your approach to strategy is pragmatic: you can move fast without all the answers, turning vague problems into clear scope, and pivoting when the situation changes. - You will Go Bold in how you lead: giving your team ownership, pushing back on processes that slow you down, and creating space for innovation alongside delivery. - You demonstrate genuine curiosity about your people and a commitment to coaching them up. You leave your team knowing more than when they joined. - You show comfort bridging technical and non-technical worlds, translating between engineers and business stakeholders without losing nuance on either side. Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

Location: Auckland Workplace: OnSite ABOUT HALTER At Halter, we’re on a mission to enable farmers and graziers to run the most productive and sustainable operations. Our customers are using Halter to break free from the time-intensive constraints of conventional practices. Imagine watching 500 cattle stand up and walk calmly towards their next break? No quad bikes, no dogs, no fences. Just a group of cattle walking at their own pace. People say it looks like magic. Our customers are revolutionizing grazing with Halter. It's changing lives and transforming an industry. People join Halter to do meaningful work. By joining us you’ll be solving challenging problems within a talented team and a culture built for high performance. Our team out-think, out-work and out-care. We’re committed to delivering real change in the world - this isn’t easy, and in truth, we love that it’s hard. We’re backed to deliver on a mission that matters by Tier 1 investors including Founders Fund https://foundersfund.com, Bessemer Venture Partners https://www.bvp.com/, BOND, https://www.bondcap.com/ DCVC https://www.dcvc.com/, Blackbird https://www.blackbird.vc/, Promus Ventures https://www.promusventures.com/, Rocket Lab’s Peter Beck and Icehouse ventures https://www.icehouseventures.co.nz/?utm_term=icehouse%20ventures&utm_campaign=Brand+Keywords&utm_source=adwords&utm_medium=ppc&hsa_acc=4064636360&hsa_cam=16902737884&hsa_grp=134004309485&hsa_ad=592971340272&hsa_src=g&hsa_tgt=kwd-1082530126230&hsa_kw=icehouse%20ventures&hsa_mt=b&hsa_net=adwords&hsa_ver=3&gclid=Cj0KCQjw2v-gBhC1ARIsAOQdKY0J0DepRVFDmjQlAkJPbZuQnLSA5UVzUzOXYiPxkjX-SeVa513_BhkaAr-MEALw_wcB. To find out more, visit our LinkedIn https://www.linkedin.com/company/halter-limited & Instagram https://www.instagram.com/lifeathalter/. ABOUT THE ROLE: Imagine building the technology that helps one of the world’s most advanced ag-tech companies scale… from the tools our teams use on the road to the systems powering our commercial and customer operations. At Halter, we’re building an ecosystem of custom applications, connected platforms, and AI-powered capabilities that help our teams work smarter and move faster. We’re looking for an Engineering Manager who gets excited about turning ambitious ideas into reliable software - and building a great engineering team along the way. Reporting to our Head of Ecosystem and AI, you’ll lead a growing team of software engineers and our Solution Architect. Your team will build across revenue, finance, marketing, localisation, and internal tools, connecting the systems and experiences that support Halter’s growth. You’ll bring strong technical judgement and real ownership of delivery. You’ll help the team make good architectural decisions, remove blockers, develop their skills, and ship work that makes a measurable difference. You’re comfortable getting into the detail, while giving your team the context and space to own their work. YOU’LL BE GREAT IF YOU BRING: - Experience leading software engineers, coaching people, managing performance, and building strong teams. - Strong engineering depth to challenge designs, review approaches, and solve complex problems. - Experience delivering applications, APIs, and integrations from discovery through to production and ongoing support. - Sound architectural judgement, balancing speed, reliability, security, and maintainability. - Experience managing delivery across multiple projects, making trade-offs clear and addressing risks early. - Ability to turn ambiguous business problems into clear technical work with product and business stakeholders. - A practical approach to engineering standards, testing, deployment, observability, and documentation. - Clear communication and collaborative energy that helps others understand technical decisions and move forward. BONUS THINGS YOU COULD BRING ALONG TO THE ROLE: - Experience building internal applications or tools for commercial and customer teams. - Experience integrating with Salesforce, finance, marketing, or other critical business systems. - Hands-on experience delivering AI-powered applications, agents, or automation. - Experience with TypeScript, Python, cloud infrastructure, and modern application architectures. - Experience supporting software across markets, including localisation. - Experience growing an engineering team in a fast-paced tech scale-up. WHAT YOUR DAY COULD LOOK LIKE: - Lead, coach and develop our software engineers and Solution Architect, setting clear expectations and supporting growth. - Own engineering delivery, turning agreed priorities into achievable plans and keeping work moving. - Partner with our Senior Product Manager and Ecosystem Manager to scope solutions, manage dependencies, and deliver connected experiences. - Guide design and architecture with our Solution Architect, keeping decisions aligned with the wider ecosystem. - Build and improve applications, integrations, services, and AI capabilities for Halter’s commercial and customer operations. - Set engineering standards that help the team ship quality, maintainable software. - Own operational health, including monitoring, incident response, and reliability improvements. - Balance new capabilities, technical debt, and platform improvements, making trade-offs clear. - Lead hiring and onboarding, building the team’s capability to deliver our roadmap. - Work with the Head of Ecosystem and AI to shape technical direction, team capacity, and investment priorities. OUR BENEFITS - Importantly, we offer an inclusive and attractive remuneration package made up of salary, benefits and an employee stock ownership plan. - Healthy body, healthy mind. We’re partnered with Southern Cross Health Insurance to support your well-being. - Our personal growth is important. Halter offers an annual $1000 self-development budget to be used for anything that fuels personal growth. - We offer 6 months of fully paid parental leave for primary caregivers, 4 weeks of fully paid secondary caregiver leave and many other parental benefits that support you and your family. - Our time to recharge is valued, we’re offered wellness leave and unlimited paid annual leave. OUR OFFICE FIRST APPROACH Humans are wired for connection. Being office first is a core pillar of our culture because in-person connections drive your growth, learning, impact, and relationships. Strong relationships make it easier to disagree, give feedback, and do meaningful work together. We're office first, not office only. Working from the office is our default, but we flex when needed. We have a high-trust culture where everyone is trusted to do what's best for Halter. Our office vibe is special, the high energy and spectacular people make work enjoyable. Your growth and impact are unlimited here, coming from solving problems, innovating, and constantly learning from each other. JOIN OUR TEAM Halter is committed to promoting a diverse and inclusive workplace — a place where we can each be ourselves and do the best work of our lives. Research shows that while men apply to jobs when they meet an average of 60% of the requirements, women and under-represented groups of candidates tend to only apply when they meet every requirement. If you think you have what it takes but don’t necessarily tick every requirement on this job description, please still get in touch and apply to Halter. We’d love to chat to see if you’ll be an epic fit! If this opportunity sounds like you, please apply below by sending through your cover letter explaining why you’re excited about this role and working at Halter, along with your CV, and we’ll be in touch! Please also feel free to check out the careers page https://www.halterhq.com/careers for more information on working at Halter and don't forget to follow us on LinkedIn https://www.linkedin.com/company/halter-limited & Instagram https://www.instagram.com/lifeathalter/. WHY OUR TEAM LOVES WORKING AT HALTER: - Work that genuinely matters. Every now and again a company comes along that transforms an entire industry and leaves the world in a better place. Our team gets to be part of something truly meaningful, helping farmers improve their livelihoods, spend more time with their families, and build more sustainable operations. - Spectacular people solving hard problems. Our culture is designed for talented people to do work that changes lives. The team is filled with diverse, kind, and driven people who push each other to do their best work. You'll be thrown into the deep end, tackling complex challenges and building something tangible that solves real problems. - You'll grow here. Autonomy, mastery, and learning define how we work. You'll have the freedom to work on interesting problems, master new skills, and continuously develop yourself, both through your role and our personal growth fund. - This isn't easy, and we love that it's hard. Working at Halter will be the most rewarding and the most challenging work of your life. We move fast, take bold bets, and work hard to reshape an entire industry. As one team member put it: "Joining Halter is a bit like strapping yourself to a rocket ship, but it's an epic journey to be a part of!"

NVIDIA is hiring PCIE Verification Engineers with at least 1 year of experience.

Location: Cyprus; Georgia; Poland; Spain; Serbia; Latvia We are looking for a Senior DevOps / Platform Engineer to develop and operate GoMining's cloud platform. The primary focus of this role is GCP and Kubernetes , infrastructure and application delivery automation, and the reliability and security of production services. You will maintain and improve our existing infrastructure, contribute to the development of the next generation of our platform, and help product teams ship changes safely and efficiently. Responsibilities Develop and operate infrastructure in GCP , including GKE, virtual machines, networking, load balancers, storage, and managed services. Manage Infrastructure as Code with Terraform : develop modules, manage state and dependencies, ensure reproducible changes, and identify configuration drift. Operate Kubernetes : upgrade clusters and platform components, configure autoscaling, workload placement, network policies, and resource allocation. Develop CI/CD and GitOps using GitLab CI and Flux / Argo CD, automating builds, checks, deployments, controlled releases, and rollbacks. Build observability across metrics, logs, distributed tracing, and actionable alerting. Define and improve SLIs/SLOs together with engineering teams. Troubleshoot production incidents and performance issues, conduct root cause analysis, and eliminate recurring failure patterns. Implement least-privilege access, environment and service isolation, secure secrets management and rotation, and infrastructure audit controls. Maintain backup processes and regularly validate recovery of critical data and infrastructure according to agreed RPO/RTO . Help engineering teams prepare services for production, including health checks, resource configuration, telemetry, and deployment procedures. Optimize cloud infrastructure usage and costs while maintaining reliability requirements. Maintain infrastructure documentation, operational runbooks, and recovery procedures. Requirements Strong hands-on experience independently operating production infrastructure and Kubernetes , including upgrades, troubleshooting, and disaster recovery. Strong experience with GCP , including GKE, Compute Engine, VPC, IAM, and Cloud Storage; good understanding of Cloud SQL, Cloud Logging, and Cloud Monitoring. Hands-on experience with Terraform , including modules, remote state, locking, importing existing resources, and safely applying infrastructure changes through CI. Deep knowledge of Kubernetes and containerization : Deployments, StatefulSets, Services, Ingress, storage, requests/limits, probes, autoscaling, RBAC, and NetworkPolicy. Experience with Helm and Kustomize . Strong Linux administration skills, preferably Debian/Ubuntu: processes, systemd, filesystems, disks, and resource troubleshooting. Strong networking fundamentals: TCP/IP, DNS, HTTP(S), TLS, routing, NAT, load balancing, and firewalls. Ability to troubleshoot connectivity issues across applications, Kubernetes clusters, networks, and cloud services. Experience building CI/CD pipelines, preferably with GitLab CI , and strong understanding of Git and GitOps principles. Understanding of runner permissions, secrets protection, and production deployment controls. Automation skills with Bash and Python , including maintainable infrastructure scripts and API integrations. Experience with monitoring, logging, and alerting using tools such as Prometheus, Grafana, or Cloud Monitoring . Practical experience operating PostgreSQL and understanding Redis and RabbitMQ, including availability, connections, replication or clustering, backup, and recovery. Strong understanding of cloud security principles: least privilege, service accounts, Workload Identity, secrets management, network segmentation, and access auditing. Ability to independently deliver infrastructure changes to a validated production result, explain technical trade-offs, and collaborate effectively with Engineering and Security teams. Nice to Have Experience with Flux CD, Argo CD, Ansible, and HashiCorp Vault . Experience with OpenTelemetry and distributed tracing. Experience migrating infrastructure between clouds or Kubernetes clusters, including database migrations with limited downtime. Experience designing disaster recovery strategies and conducting recovery exercises. Cloud cost optimization and capacity planning experience. Experience with DigitalOcean, Hetzner, or AWS . Ability to read and troubleshoot JavaScript / TypeScript applications. Experience operating financial or payment services with strict requirements around access control, auditing, reliability, and data integrity. Benefits Professional growth: support for courses, conferences, and English learning (up to 100% coverage). Work-life fit: remote or hybrid format with flexible hours across international teams. Paid leave: up to 20 vacation days +  8 company holidays + 5 personal days per year Recognition programs: structured performance reviews and team awards. Team culture: retreats in international locations (for example, company apartments in Cyprus).