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Shield AI ищет руководителя инженерного отдела по воздушным аппаратам, который будет отвечать за проектирование, интеграцию, испытания, управление техническими рисками и подготовку производства летательных аппаратов. Кандидат должен обладать опытом в таких областях, как цепочки поставок, дизайн воздушных судов, управление поставщиками, системная интеграция, производство, аэрокосмическая инженерия, наука о полёте, управление рисками, летные испытания, верификация и валидация, управление полётом, аэродинамика, двигатели, качество, конструкция и авионика.

Задачи: — строить и запускать в эксплуатацию инструменты AI, шлюзы, интеграции и механизмы контроля использования. Требования: — опыт работы с backend, LLM, API Gateway, Azure OpenAI, распределёнными системами, облачной инженерией. — знание Go и Python. — опыт настройки прокси, работы с API, ключами API, сетями, инфраструктурой инференса, деплоем моделей, алертингом. — навыки платформенной инженерии и интеграции. Условия: — null.

Location: New York; San Francisco Workplace: Hybrid ABOUT ALCHEMY Alchemy is the Web3 infrastructure and developer platform that powers millions of users and the world’s most innovative blockchain applications. From enabling $1+ trillion in financial transactions worldwide to scaling L2s and enabling DeFi, Alchemy provides the infrastructure and tools developers need to build reliable, scalable, and accessible experiences. Trusted by companies like JPMorgan, Stripe, Visa, Franklin Templeton, Nike, and backed by a16z, Coatue, Silver Lake, Lightspeed, and Stanford University, Alchemy is building the foundational layer for a decentralized and AI-enabled Web3 ecosystem. For more information, visit alchemy.com http://alchemy.com. THE ROLE Build and run the internal data platform that helps Alchemy understand product usage, revenue, and the cost of serving customers. The existing Data Engineer intake centers on ingestion, Snowflake operations, workflow orchestration, data quality, and collaboration with analytics partners. You will own ingestion, schema changes, and checks that show whether shared datasets are current and correct. You will work with analytics engineers and data scientists to define those datasets for reporting, analysis, and AI-assisted tools. WHAT YOU WILL DO - Build batch and streaming pipelines that connect operational databases, product events, billing systems, and external sources to the internal data platform. - Make ingestion recoverable through change-data capture, schema-change handling, idempotent processing, and safe backfills. - Operate and improve Snowflake, including access controls, workload management, query performance, and compute and storage costs. - Improve orchestration and deployment workflows so engineers can test, ship, and debug pipelines safely. - Build data-quality checks that detect stale, missing, duplicated, or inconsistent records before they reach downstream consumers. - Work with analytics partners on shared data models, source definitions, and documentation. Make dataset ownership and upstream dependencies clear. - Reduce recurring manual work and build reusable tools for self-service data access. - Participate in production support and incident response for pipelines and the data platform. Restore data flow, reconcile affected datasets, and fix the causes of recurring failures. WHAT WE ARE LOOKING FOR - Experience independently building and operating production data pipelines and the infrastructure around them. - Strong SQL and Python skills, including testing, debugging, and maintainable software design. - Experience with Snowflake or a comparable warehouse, including performance tuning and access management. - Experience with workflow orchestration and transformation tools such as Airflow and dbt, or equivalent systems. - Understanding of data modeling, incremental processing, schema evolution, and data-quality testing. - The ability to trace a data discrepancy from a downstream report back to its source, explain the cause, and fix it. - Good judgment about stakeholder needs: turn recurring requests into reusable datasets or tooling, and make trade-offs clear. Blockchain experience is not required. HELPFUL EXPERIENCE - Kafka, database replication, or change-data-capture systems. - Apache Iceberg, Spark, Trino, or other lakehouse and query technologies. - Infrastructure as code, data observability, lineage, and disaster recovery. - Usage metering, billing and revenue data, or semantic layers for self-service analytics. WHAT SUCCESS LOOKS LIKE Within three months: - You own a production pipeline and have shipped an improvement to its freshness, reliability, or operating cost. - Downstream users can see whether its data is current, recovery procedures have been tested, and a recurring manual request has become a reusable dataset or tool. BENEFITS & PERKS 🏥 Private Health Insurance 💪 Gym Reimbursement 🚅 Commuter Benefits 🌴 Flexible Time Off 🥙 In-Office Group Meals 🧠 Learning & Development Stipend 🌎 Company Sponsored Conferences & Events 🎧 Books & Audiobook subscription with Bookster https://landing.bookster.ro/

Location: Remote, Global ABOUT THE ROLE We are seeking a platform engineer to join our Compute team. This team owns the critical systems that power project provisioning, scaling, and the compute that our users rely on every day. You’ll work on the core platform that ensures Supabase can seamlessly scale across multiple regions, handle high-volume workloads, and provide low-latency, highly available compute services. You'll design, build, and operate systems that are both robust and highly automated — enabling us to provision new projects reliably at scale, optimize resource utilization, and deliver a seamless experience to the millions of databases which we manage. WHAT YOU’LL BE RESPONSIBLE FOR: - Help build and maintain the Supabase Cloud offering; - Design and implement systems to provision, scale, and manage the multi-region compute workloads powering Supabase projects; - Own the full lifecycle of compute orchestration: project creation, warm pools, autoscaling, resizing, and resource optimization; - Improve automation and observability across the compute stack to ensure high availability and performance; - Improve our system architecture to reduce costs while balancing security, reliability, and performance; - Collaborate cross-functionally with other teams to help leverage compute as a core platform offering; - Participate in on-call rotations, incident response, and post-incident reviews; - Resolve escalated support issues, while also identifying and resolving systemic issues across the platform. YOU MIGHT BE A GOOD FIT IF YOU: - Have strong software engineering skills (Go and Typescript required); - Experience building and operating cloud infrastructure or distributed systems at scale; - Have 5+ years experience with cloud infrastructure (AWS required, additional experience with GCP and Azure is a plus) - particularly compute, networking, and storage services; - Have 3+ years experience working with building custom Kubernetes controllers, and operating large-scale (tens-to-hundreds of thousands of pods) clusters; - Are knowledgable about networking and multi-region infrastructure design; - Are familiar with Postgres; - Have experience with Infrastructure as Code tools (Pulumi highly preferred, Terraform/CDK etc acceptable) - Have experience working with QEMU, KVM, and NAS is a plus; - Have experience with being part of on-call rotations for large production system; WHAT WE OFFER - Fully Remote We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world. - ESOP Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together. - Tech Allowance Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work. - Health Benefits Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us. - Annual Off-Sites Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year. - Flexible Work We operate asynchronously and trust you to manage your own time. You know what needs to be done and when. - Professional Development Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth. ABOUT THE TEAM Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. - ~400 team members - 60+ countries - 20+ languages spoken - Over $1B raised (including our $500M Series F) - 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

Задачи: — Быть активным участником инженерных проектов, помогать в их выполнении и предвидеть проблемы с поставками. — Определять долгосрочные позиции, критические материалы и сложные детали как можно раньше и обеспечивать их наличие до того, как они станут узкими местами для тестирования и сборки. — Действовать при угрозах графику прототипа, связанных с мощностями обработки, доступностью материалов, очередями на специальные процессы или поздними изменениями в дизайне. — Быть ключевым связующим звеном между инженерией и производством, сообщать о рисках цепочки поставок и критических деталях для успешной передачи в производство. — Поддерживать успех каждой итерации инженерного прототипа и готовить производство к запуску и массовому производству. — Обеспечивать поддержку быстро меняющихся инженерных команд, работающих над несколькими аппаратными проектами. — Переводить концепции, изменяющиеся спецификации и изменения в дизайне в конкретные шаги по закупкам с минимальными задержками. — Предоставлять инженерам актуальную информацию о доступности материалов, компонентов и вариантах быстрого производства. — Выявлять проблемы с поставками до того, как они станут блокирующими, и предлагать обходные пути. Требования: — Проактивность и ориентация на решение проблем. — Глубокое понимание процессов механического производства, материалов и прототипирования аппаратного обеспечения. — Умение работать в условиях неопределенности и предвидеть проблемы. Условия: — Постоянная работа в офисе в Эспоо, Финляндия. — Работа в глобальной команде ICEYE, лидера в области спутниковой разведки. — Подчинение менеджеру цепочки поставок R&D. — Требуется прохождение проверки безопасности (включая SUPO, если необходимо).

Задачи: — Решение сложных технических задач и разработка качественных программных систем с применением современных технологий. — Работа с данными в production-среде. — Поиск первопричин сбоев. — Преобразование и валидация больших объёмов данных. — Взаимодействие с REST-API. — Загрузка и выгрузка данных. — Работа с сериализованными и сжатыми форматами. Требования: — От 2 лет опыта с Python и библиотеками для работы с данными (pandas, multiprocess, Google Cloud SDK). — От 2 лет в ETL/ELT-технологиях (REST API, GraphQL, DBT) и оркестрации пайплайнов (Airflow, Astronomer, DBT Cloud). — Практический опыт со Snowflake. — Уверенное владение SQL (SQL Server, Oracle, MySQL, BigQuery, Snowflake). — Работа с форматами JSON, AVRO, XML, CSV, а также со сжатыми и закодированными файлами. — Навыки загрузки данных через REST-API и выполнения трансформаций. — Достаточный уровень английского для работы в международной среде. — Плюсом — опыт проектирования пайплайнов в облачной архитектуре, работы с CI/CD и GIT.

Location: Remote, Canada; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As Director, Analytics Engineering, you'll lead a team of 8 and report to the VP of Data & Insights. You set direction across the data organization, stay close enough to the work to guide technical decisions credibly, and partner with Data Engineering, Data Science, IT, and business leaders. You will have three mandates: Build trusted, AI-ready self-service. Deliver a semantic model that answers business questions correctly, with the telemetry, evals, and model flexibility to prove it and keep costs in check. Set the strategy for how GitLab accesses data. Own the data models, BI tools, and AI access patterns (Claude, MCP servers, Slack agents) that put trusted data in everyone's hands. Build data applications the whole company relies on. Ship production-grade apps that combine trusted data, APIs, and AI to answer questions dashboards can't. What you'll do Build and own a trusted semantic model, with governed metrics and business definitions, that answers business questions consistently across every tool Build evals and ground-truth datasets that measure answer quality, and use them to drive improvements and catch regressions Instrument telemetry to see who uses the semantic model and AI tools, what they ask, and where they get stuck Build a model-selection harness so GitLab can route work across LLMs and stay flexible on cost and quality Own data modeling and curated datasets for self-service, with the ownership, data contracts, testing, and documentation that make them AI-ready Define the AI data access strategy: when to use BI, Claude, MCP servers, or Slack agents, with the governance and security to keep access trusted and reliable Own the enterprise BI and self-service tools strategy (e.g., Tableau, Omni), including evaluation, adoption, and cost Build self-service capabilities, such as Claude skills, documentation, and guided workflows, that help people find and use data on their own Build and own company-wide data applications, from Claude-built single-page apps to apps inside BI tools, that combine Snowflake data, API calls, AI-powered deep dives, and write-back to Postgres or Snowflake Set engineering standards for data apps (security, authentication, testing, deployment, and monitoring) so they're reliable at company scale Set a long-range roadmap tied to company strategy, and a lightweight operating model that balances urgent stakeholder needs with investment in reusable data products and tech-debt reduction Hire, coach, and retain a high-performing team of 8: build career paths, develop leaders, distribute ownership, and recognize great work Act as customer zero for GitLab and GitLab Duo in data workflows, sharing feedback with Product and Engineering What you'll bring 12+ years in analytics engineering, data engineering, or BI, including 5+ years leading teams and 2+ years managing managers or senior leads Deep expertise in data modeling and semantic layers (e.g., dbt Semantic Layer, Snowflake semantic views, LookML, Cube), and expert dbt, including testing and CI/CD across a multi-team project Hands-on experience building LLM-powered data access (text-to-SQL, agents, MCP servers), including evals and telemetry for answer quality, and advanced use of AI coding agents such as Claude Code Expert SQL and strong Snowflake experience; working knowledge of Python Strong data governance experience: data quality, lineage, certified datasets, and access controls (RBAC, row access and masking policies) Track record of leading cross-functional data initiatives from strategy through adoption and measurable business impact, including enterprise BI and self-service at scale Systems thinker who sees how models, pipelines, and architecture decisions connect, and designs for second-order effects Exceptional communicator who writes clear technical specs, sets a clear vision, makes trade-offs visible, and influences executives and peers across the company Pragmatic in ambiguity: makes sound decisions on emerging technology and ships the right next version rather than waiting for the ideal end state Able to use GitLab, thrive in an all-remote, asynchronous company, model GitLab's remote working competencies, and work in line with GitLab's values Nice to Have Experience with LLM routing or gateway tools and managing model costs Experience with Tableau, Omni, or a BI platform migration Experience with web app development (e.g., React, TypeScript) and Postgres Experience owning finance or revenue-critical data (e.g., ARR, consumption) where accuracy and auditability are non-negotiable About the Team Analytics Engineering makes GitLab's data trusted, easy to find, and ready for anyone to use, whether they ask a dashboard, Claude, or a Slack agent. We own the curated data models, the semantic layer, the self-service tools, and the data applications that let teams answer their own questions. AI is changing how people get to data. Questions that once went through an analyst now go straight to AI tools, so the answers are only as good as the data models and business definitions behind them. Our job is to make those answers correct, consistent, and measurable. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $139,200 — $285,600 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: Brazil, Colombia Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. About the Client Our customer is a leading education technology company that develops digital platforms and software solutions to support learning and improve educational experiences. The organization combines technology, data, and innovation to deliver scalable solutions to users and institutions worldwide. What You’ll Do Design, develop, and maintain reliable, scalable data pipelines and ELT processes using SQL and dbt. Build, optimize, and maintain data transformations, ensuring data quality, consistency, and reliability. Manage and maintain infrastructure using Terraform and infrastructure-as-code practices. Develop and support web applications and services using Node.js, TypeScript, GraphQL, and React. Collaborate with data, product, and engineering teams to deliver integrated data and application solutions. Contribute to the monitoring, troubleshooting, and continuous improvement of data pipelines, applications, and infrastructure. Participate in code reviews, technical discussions, and engineering best practices using GitHub and related tools. Participate in the on-call rotation, serving as the primary on-call engineer for one week out of every four and as backup on-call engineer for an additional week out of every four. What You Bring Strong hands-on experience with data engineering and ELT processes, including advanced SQL and dbt for building and maintaining data transformations and pipelines. Practical experience with Terraform and infrastructure-as-code practices for managing and maintaining technical environments. Proven web application development experience with Node.js, TypeScript, GraphQL, and React, with the ability to contribute across backend and frontend components. Strong problem-solving and troubleshooting skills, with a focus on reliability, maintainability, and production support. Ability to collaborate effectively with distributed, cross-functional teams and work with colleagues operating in the US Mountain Time zone. Availability to participate in the on-call rotation, including one primary on-call week and one backup on-call week in every four-week cycle. Nice to have Experience with Snowflake and AWS cloud services. Familiarity with Apache Airflow for workflow orchestration, Looker for analytics and business intelligence, and Python for scripting or data engineering. Experience with GitHub-based development workflows, including version control, pull requests, and collaborative code reviews. English level Intermediate/Upper-Intermediate Legal & Hiring Information Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more Reasonable accommodations are available to enable individuals with disabilities to perform essential functions Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs Compensation details are shared with candidates at the early stage of the recruitment process. The offer is not binding until a signed contract is in place. Our AI-Enabled Screening Process As an AI-first company, Exadel uses an AI recruiter to conduct a brief initial screening for this highly specialized position. This conversation helps us understand each applicant’s relevant experience and alignment with the role’s core requirements. The AI recruiter supports the process but does not make the final hiring decision. Candidates who successfully complete the initial screening will be connected directly with a member of our Talent team for the next step. If you require an accommodation or an alternative screening format, please let us know. Your Benefits at Exadel Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details. International projects In-office, hybrid, or remote flexibility Medical healthcare Recognition program Ongoing learning & reimbursement Well-being program Team events & local benefits Sports compensation Referral bonuses Top-tier equipment provision Exadel Culture We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Location: London Workplace: Hybrid Why loveholidays? We’re on a mission to open the world to everyone, giving our customers unlimited choice, unmatched ease and unmissable value for their next getaway. Our trailblaze together culture is what drives our success, powered by our people and the way they work. Using progressive technology, we drive cutting-edge innovation and improve how our customers discover, book and experience their holidays. You’ll have the opportunity to accelerate your growth through meaningful challenges, new experiences and the freedom to shape your own path. You’ll create impact for our future by taking ownership, contributing to shared goals and helping shape what comes next, all as part of our enhanced international community of talented, collaborative and passionate teams.   The difference you’ll make: You’ll sit in the Applied AI who are part of the wider AI Centre of Excellence reporting to the Lead Applied AI Engineer. You’ll work closely with our business verticals, engineering, security, vendors and business stakeholders to build, administer and improve the AI-enabled systems and SaaS platforms that support our customers and colleagues. Together, the Centre of Excellence teams builds and operates applied and agentic AI workflows, SaaS services, integrations and data pipelines to deliver the business objectives of the supported verticals. You’ll contribute to production services from day one, developing your skills while improving reliability, automation and operational outcomes. The team sits within Business IT & AI Operations, providing the technical expertise, governance and operational ownership that help loveholidays scale intelligent automation and well-run business systems safely and effectively. Your day-to-day: - Administer and continuously improve a rangeSaaS platforms and AI-enabled services, including configuration, access, environments, integrations and lifecycle management. - Build and maintain applied and agentic AI workflows and automation pipelines that connect models, tools, business data, APIs and SaaS systems. - Use Google ADK or similar frameworks to build, test and iterate on tool-using agents and AI-powered automations. - Monitor service health, usage, cost and performance; lead testing, evaluation and incident triage to improve reliability and prevent recurring issues. - Partner with product, engineering, security, vendors and business teams to translate needs into effective platform configurations, integrations and automations. - Document configurations, dependencies and runbooks, applying secure change-management, governance and operational practices. Your skillset: - SaaS Administration: Experience administering cloud-based business systems, including configuration, user access, environments, integrations, release management and vendor support. - Applied AI & Agentic Workflows: Experience building agentic workflows that combine models, tools and business data, including orchestration, retrieval-augmented generation and evaluation. Familiarity with Google ADK or similar frameworks is desirable. - API & Data Integration: Strong knowledge of REST APIs, webhooks and event-driven or scheduled pipelines for connecting SaaS platforms, AI services and backend systems. - Familiarity with cloud environments, preferably Google Cloud Platform, CI/CD, observability, incident management and secure operational practices. The interview journey: - Intro with a member of the Talent Acquisition team - 30 mins - 1st stage video interview with Lead Applied AI Engineer - 1 hour - Applied AI and SaaS administration task - Final stage with Director of Applied AI and senior stakeholders - 1 hour Perks of joining us: - Company pension contributions at 5% - Individualised training budget for you to learn on the job and level yourself up - Discounted holidays for you, your family and friends - 25 days of holidays per annum (plus 8 public holidays) increases by 1 day for every second year of service, up to a maximum 30 days per annum - Ability to buy and sell annual leave - Cycle to work scheme, season ticket loan and eye care vouchers Our commitment to inclusion: At loveholidays, we focus on creating an inclusive environment where everyone can contribute, grow and succeed. We value the different perspectives, experiences and ideas each person brings, because they help us work better together, challenge our thinking and make stronger decisions. As we continue to grow and evolve, we want everyone to feel supported and able to do their best work. We’re also committed to making our hiring process accessible, so please let our Talent Acquisition team know if you need any adjustments at any stage.

Location: Mapbox Poland Workplace: Remote Mapbox is the leading real-time location platform for a new generation of location-aware businesses. Mapbox is the only platform that equips organizations with the full set of tools to power the navigation of people, packages, and vehicles everywhere. More than 4 million registered developers have chosen Mapbox because of the platform’s flexibility, security and privacy compliance. Organizations use Mapbox applications, data, SDKs and APIs to create customized and immersive experiences that delight their customers.  WHAT WE DO The Navigation team https://www.mapbox.com/navigation at Mapbox develops and operates web services powering virtually all of Mapbox’s strategic navigation initiatives in consumer, automotive, and logistics verticals. We are a highly multidisciplinary organization, with work spanning distributed systems on AWS to geospatial localization, traffic telemetry, and mapping. Collectively we are revolutionizing in-car experiences with technology to build fast, industry-leading maps and navigation for any vehicle. We’ve launched products such as MapGPT https://www.mapbox.com/mapgpt, Mapbox for EV https://www.mapbox.com/ev, and we’re enhancing the visual experience of in-vehicle navigation with 3D styling with our new Mapbox Standard through web and mobile SDKs. Mapbox has worked with automotive partners https://www.mapbox.com/automotive— including BMW, Toyota, and GM — to bring the best aspects of mobile app development into in-vehicle navigation and infotainment. - Mapbox Blog: Introducing 3D Live Navigation https://www.mapbox.com/blog/mapbox-3d-navigation - Mapbox Blog: Route Notifications Improve Driver Safety https://www.mapbox.com/blog/route-notifications-improve-driver-safety - Mapbox Newsroom: AI Features in New Navigation SDK https://www.mapbox.com/press-releases/mapbox-unveils-ai-features-in-new-navigation-sdk As AI becomes embedded in modern engineering workflows, we value engineers who can thoughtfully integrate AI into design, development, and decision-making. Our interview process will include discussion of how you use AI in your engineering workflow. WHAT YOU’LL DO As a Machine Learning Engineer III on the Routing Cost team, you will lead the design, development, and delivery of highly trafficked recommendation systems for our routing cost engine. Your technical contributions will include: - Lead the engineering team(s) to execute end-to-end feature implementation within the larger navigation organization (~80 engineers). - Design and build new ML and data pipelines, as well as optimizing existing ML and data pipelines. - Build tools for automated quality assurance and data exploration. - Leverage geospatial algorithms to optimize pipelines, as well as creating automated tuning and outlier detection algorithms. - Partner with data scientists to make improvements to our models for determining patterns in movement and/or traffic. - Mentor colleagues and participate in code and design reviews. - Participate in an on-call rotation to ensure our systems remain available to customers 24/7. Team members alternate as the on-call primary responder, which may require immediate response outside normal working hours, including weekends. WHAT WE BELIEVE ARE IMPORTANT TRAITS FOR THIS ROLE - 8-10+ years of backend and ML experience: Extensive hands-on experience showcasing expertise and a strong track record in the engineering field. - Technical knowledge: Extensive experience with Python, distributed processing pipelines (Hadoop, Spark, Airflow, Dask), and very large datasets – statistical analysis, data quality control, optimizing storage. - Cloud proficiency: Extensive experience with cloud and infrastructure services, including, as well as deploying and managing infrastructure in cloud environments. - Operational excellence: You drive a culture of quality and continuous improvement in your organization. Strong passion for clean code and robust architecture, with a drive to elevate engineering practices and design standards across the team. - Ownership & execution: Own the technical vision, lead the strategy and guide the team to execute towards building the future of our routing cost engine. - Customer focus: You care deeply about your customers and their problems, and you work tirelessly to innovate on their behalf. - Growth mindset: Have the humility to accept mistakes, learn and grow from them. - Mentorship: Experience mentoring and leading engineering teams developing skill sets and career growth. - Strong written and vocal communication skills: You can talk and write about complex ideas concisely to a wide audience. You are able to lead and resolve org-wide technical discussions and are able to collaborate and include input from cross-functional teams (security, devops, data, compliance and product). - Data informed mindset: You believe in the value of data informed decision making and strive to measure things that are not straight forward but essential. You also have the right instincts to make speedy decisions in the absence of perfect & comprehensive data WHAT WE VALUE In addition to our core values https://www.mapbox.com/about/values/, which are not unique to this position and are necessary for Mapbox leaders: - We value high-performing creative individuals who dig into problems and opportunities. - We believe in individuals being their whole selves at work. We commit to this through supportive health care, parental leave, flexibility for the things that come up in life, and innovating on how we think about supporting our people. - We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company. - We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply. Our annual compensation for this role ranges from $102.000 - $153.000 (salaries are in USD). Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of the role). By applying for this position, you acknowledge that you have received the Mapbox Non-US Privacy Notice https://www.mapbox.com/legal/applicant-privacy-notice/ for applicants, which is linked here.  Completing this application requires you to provide personal data, such as your name and contact information, which is mandatory for Mapbox to process your application.  We are committed to a fair and equitable hiring process. We do not discriminate against any protected class.

Требования: — Опыт в разработке ПО от 8 лет — Сильная экспертиза в бэкенде, инфраструктуре данных или прикладном AI — Опыт в архитектуре, интеграциях API и техническом лидерстве — Английский C1+ О компании: Ранний travel tech продукт, который делает бонусы программ лояльности ценнее для путешественников.

Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. WHOOP is seeking an NPI Quality Engineer II, Hardware to support Product Quality activities for hardware development programs from concept through launch. As a member of the Product Quality organization, you will partner closely with Hardware Engineering, Manufacturing Engineering, Supplier Quality, Reliability, Operations, and global manufacturing partners to help ensure products are designed, validated, and launched with exceptional quality. You will support quality planning, design and manufacturing risk management, validation, and launch-readiness activities while developing technical expertise in Product and NPI Quality. RESPONSIBILITIES: - Support Product Quality activities for assigned hardware development programs, components, or subsystems throughout development, validation, manufacturing readiness, and product launch. - Partner with Product Management and Systems Engineering to help translate Voice of Customer requirements into measurable product and engineering requirements. - Work cross-functionally with Hardware Engineering, Manufacturing Engineering, Supplier Quality, Field Quality, Reliability, Test Engineering, Operations, and manufacturing partners to identify potential failure modes and quality risks early in product development and track them through resolution. - Support and facilitate quality planning activities including DFMEA, CTQ definition, reliability planning, validation and verification, process capability, measurement system analysis, and launch-readiness reviews. - Analyze engineering and manufacturing data to identify product and process risks and support data-driven decision making. - Partner with Supplier Quality to support supplier and contract-manufacturer quality activities, including engineering drawing reviews, design-file reviews, control plans, inspection strategies, and process capability assessments. - Apply structured problem-solving methodologies to investigate product and manufacturing failures, support root-cause analysis, and drive corrective and preventive actions. - Support engineering builds and NPI activities, including identification, documentation, prioritization, and closure of quality issues. - Monitor product and process quality metrics and communicate significant trends, risks, and issues to the Product Quality team and cross-functional stakeholders. - Participate in cross-functional program and technical reviews, providing objective quality data and supporting risk and launch-readiness assessments. - Document lessons learned and help ensure relevant findings from development, validation, manufacturing, and field performance are incorporated into future product-development activities. - Contribute to the continuous improvement of Product Quality processes, tools, templates, and standards. - Willing and able to travel up to 15% internationally to partners, suppliers, and contract manufacturers. QUALIFICATIONS: - Bachelor's degree in Mechanical Engineering, Electrical Engineering, Manufacturing Engineering, Industrial Engineering, Quality Engineering, or a related technical discipline. - 3–5+ years of experience in Product Quality, NPI Quality, Manufacturing Quality, Product Engineering, or related engineering roles supporting consumer electronics, wearables, medical devices, or similarly complex hardware. - Experience supporting hardware products through one or more phases of product development, validation, manufacturing readiness, and/or launch. - Working knowledge of quality methodologies including DFMEA, PFMEA, CTQ, DOE, SPC, MSA, GR&R, root-cause analysis, CAPA/8D, and statistical quality methods. - Experience analyzing engineering and manufacturing data and applying structured problem-solving techniques. - Experience working with suppliers or manufacturing partners, preferably in a high-volume manufacturing environment. - Strong analytical and problem-solving skills with the ability to use objective data to identify and communicate product and manufacturing risks. - Effective written and verbal communication skills with the ability to collaborate across engineering and operations teams. - Ability to operate effectively in a fast-paced, collaborative environment while managing assigned priorities and deliverables. - Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions. This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.   Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.   WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/ to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.   The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.   At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.   The U.S. base salary range for this full-time position is $120,000 - $160,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.   In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.   These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

Location: Finland; Mapbox Helsinki Workplace: Remote Mapbox is the leading real-time location platform for a new generation of location-aware businesses. Mapbox is the only platform that equips organizations with the full set of tools to power the navigation of people, packages, and vehicles everywhere. More than 4 million registered developers have chosen Mapbox because of the platform’s flexibility, security and privacy compliance. Organizations use Mapbox applications, data, SDKs and APIs to create customized and immersive experiences that delight their customers.  WHAT WE DO The Navigation team https://www.mapbox.com/navigation at Mapbox develops and operates web services powering virtually all of Mapbox’s strategic navigation initiatives in consumer, automotive, and logistics verticals. We are a highly multidisciplinary organization, with work spanning distributed systems on AWS to geospatial localization, traffic telemetry, and mapping. Collectively we are revolutionizing in-car experiences with technology to build fast, industry-leading maps and navigation for any vehicle. We’ve launched products such as MapGPT https://www.mapbox.com/mapgpt, Mapbox for EV https://www.mapbox.com/ev, and we’re enhancing the visual experience of in-vehicle navigation with 3D styling with our new Mapbox Standard through web and mobile SDKs. Mapbox has worked with automotive partners https://www.mapbox.com/automotive— including BMW, Toyota, and GM — to bring the best aspects of mobile app development into in-vehicle navigation and infotainment. - Mapbox Blog: Introducing 3D Live Navigation https://www.mapbox.com/blog/mapbox-3d-navigation - Mapbox Blog: Route Notifications Improve Driver Safety https://www.mapbox.com/blog/route-notifications-improve-driver-safety - Mapbox Newsroom: AI Features in New Navigation SDK https://www.mapbox.com/press-releases/mapbox-unveils-ai-features-in-new-navigation-sdk As AI becomes embedded in modern engineering workflows, we value engineers who can thoughtfully integrate AI into design, development, and decision-making. Our interview process will include discussion of how you use AI in your engineering workflow. WHAT YOU’LL DO As a Machine Learning Engineer III on the Routing Cost team, you will lead the design, development, and delivery of highly trafficked recommendation systems for our routing cost engine. Your technical contributions will include: - Lead the engineering team(s) to execute end-to-end feature implementation within the larger navigation organization (~80 engineers). - Design and build new ML and data pipelines, as well as optimizing existing ML and data pipelines. - Build tools for automated quality assurance and data exploration. - Leverage geospatial algorithms to optimize pipelines, as well as creating automated tuning and outlier detection algorithms. - Partner with data scientists to make improvements to our models for determining patterns in movement and/or traffic. - Mentor colleagues and participate in code and design reviews. - Participate in an on-call rotation to ensure our systems remain available to customers 24/7. Team members alternate as the on-call primary responder, which may require immediate response outside normal working hours, including weekends. WHAT WE BELIEVE ARE IMPORTANT TRAITS FOR THIS ROLE - 8-10+ years of backend and ML experience: Extensive hands-on experience showcasing expertise and a strong track record in the engineering field. - Technical knowledge: Extensive experience with Python, distributed processing pipelines (Hadoop, Spark, Airflow, Dask), and very large datasets – statistical analysis, data quality control, optimizing storage. - Cloud proficiency: Extensive experience with cloud and infrastructure services, including, as well as deploying and managing infrastructure in cloud environments. - Operational excellence: You drive a culture of quality and continuous improvement in your organization. Strong passion for clean code and robust architecture, with a drive to elevate engineering practices and design standards across the team. - Ownership & execution: Own the technical vision, lead the strategy and guide the team to execute towards building the future of our routing cost engine. - Customer focus: You care deeply about your customers and their problems, and you work tirelessly to innovate on their behalf. - Growth mindset: Have the humility to accept mistakes, learn and grow from them. - Mentorship: Experience mentoring and leading engineering teams developing skill sets and career growth. - Strong written and vocal communication skills: You can talk and write about complex ideas concisely to a wide audience. You are able to lead and resolve org-wide technical discussions and are able to collaborate and include input from cross-functional teams (security, devops, data, compliance and product). - Data informed mindset: You believe in the value of data informed decision making and strive to measure things that are not straight forward but essential. You also have the right instincts to make speedy decisions in the absence of perfect & comprehensive data WHAT WE VALUE In addition to our core values https://www.mapbox.com/about/values/, which are not unique to this position and are necessary for Mapbox leaders: - We value high-performing creative individuals who dig into problems and opportunities. - We believe in individuals being their whole selves at work. We commit to this through supportive health care, parental leave, flexibility for the things that come up in life, and innovating on how we think about supporting our people. - We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company. - We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply. By applying for this position, you acknowledge that you have received the Mapbox Non-US Privacy Notice https://www.mapbox.com/legal/applicant-privacy-notice/ for applicants, which is linked here.  Completing this application requires you to provide personal data, such as your name and contact information, which is mandatory for Mapbox to process your application.  We are committed to a fair and equitable hiring process. We do not discriminate against any protected class.

Location: Vladivostok Workplace: onsite ABOUT US Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game.   For more information, visit xsolla.com.   ABOUT YOU We are looking for a Junior Developer (AI Engineering) to join the Xsolla Partner Network (XPN) team, a platform that connects game studios and publishers with content creators. The position involves participation in all stages of work on an automated content generation system: from stabilising the existing vertical video pipeline for YouTube Shorts, TikTok and Instagram Reels to developing the agentic architecture, launching the virtual AI creator direction and building analytics on the results. Working with the team means applying cutting-edge generative models and agentic tools to a real production product every day, seeing the direct effect of your work in content metrics, and learning from the inside how the games industry, the creator economy and content-driven game promotion work. The developer will work with a live system that has a real audience and measurable results, make technical decisions independently, build expertise in generative AI and take on the role of the project's technical owner as it grows. Responsibilities Take over the existing vertical video generation pipeline (script → voiceover → visuals → subtitles → editing → auto-posting → tracking links) for YouTube Shorts, TikTok and Instagram Reels, understand it from the docs and code, and bring it to stable operation. Grow the pipeline: improve content quality and virality, scale up generation volume, reduce cost and turnaround time per video. Keep track of new generation models and services (video, image, voice, LLM), test them quickly and replace outdated parts of the pipeline with better or cheaper ones. Launch and develop the virtual AI creator direction: a consistent character, voice, style and content plan. Design and improve agents: write and debug prompts and sub-agent roles, validation between phases, context and cost control. Build a dashboard for running generation and tracking content analytics (views, clicks, conversions, cost per video). Automate publishing: platform integrations, posting from mobile devices, scaling channels. Write clean, testable, documented code, including unit and integration tests. Requirements Solid Python, basic bash. Hands-on experience with LLM APIs (Claude, OpenAI, etc.) and agentic pipelines: a real project, pet project or hackathon entry you can show and talk through. Experience using Claude Code, Cursor or similar tools as a working environment, not just as autocomplete. Understanding of prompt engineering basics: defining an agent's role, limiting context, getting stable structured output. Understanding of Git, team development and Docker basics. Ability to work with REST APIs and webhooks, basic understanding of databases (SQL). Understanding of vertical content: games, creators, streams, TikToks, Shorts, how video discovery works, what shadowbans are, how mobile posting farms are set up. A big plus if this is your hobby: your own channel, editing, streaming, experiments with AI generation. Ownership: the ability to take a task end to end and deliver a result without external supervision. Initiative: your own proposals on improving the pipeline, new models and automation, and the readiness to implement them yourself. Ability to figure out someone else's system from code and documentation, reconstruct the logic and ask the right questions. Independence in technical decisions and openness in communication: flag problems immediately. Product thinking: measuring results by content metrics (views, retention, clicks) and cost per video. Ability to explain the system's capabilities and limitations to non-technical colleagues. Experimental mindset: fast hypothesis testing and the willingness to drop what did not work. Desire to grow with the project: from stabilising the current pipeline to becoming its technical owner. English at the level of reading technical documentation (Intermediate+). Nice to have Experience with video and image generation via API ( fal.ai , Kling, Runway, Seedance, Nano Banana, etc.), TTS and speech recognition (Whisper and similar). ffmpeg: assembly, normalisation, subtitles, overlays. Experience building reliable calls to paid APIs: retries, idempotency, cost tracking. n8n or other workflow tools. Telegram bots, YouTube / TikTok / Instagram / Discord APIs. Android / mobile device automation. Supabase or PostgreSQL. Experience with GCP, Docker, Kubernetes. Observability and monitoring (Datadog, OpenTelemetry). Your own channel, pet projects, open-source experience or hackathon participation. Benefits   Convenient working tools: New Mac laptop and any other necessary equipment for your efficient work. Google Workspace, Atlassian, Jira, Slack   Professional growth: Exchange of experience between employees within the company Opportunity for professional growth within the company and department Obtaining expertise in various areas and products of the company   More perks Possibility of flexibility working Access to the corporate library No dress code Comfortable and new office environment The duties and responsibilities of this position may evolve over time to support the organization’s goals and individual growth. This job description is intended to outline the general nature and level of work being performed and is not intended to be an exhaustive list of all duties, responsibilities, and qualifications required. By submitting your application, you consent to Xsolla conducting background checks, where permitted by law, after the final interview stage. All checks will comply with local regulations, and your information will be handled confidentially. Xsolla takes your privacy seriously and will not sell or externally distribute any personal data received during the hiring process. In accordance with applicable data protection laws, Xsolla is committed to protecting your personal information and respecting your privacy. For any inquiries related to data privacy, please contact: careers@xsolla.com Explore more opportunities at: https://xsolla.com/careers

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. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. We’re looking for a Machine Learning Engineering Manager to join us in London on a hybrid basis (3 days a week). In this role, you’ll lead the team that owns intelligence across our ordering experience, from store page and item selection through cart, upsell and checkout, plus bundling. Personalisation is one of the biggest levers we have to drive value to our customers, and your team will make the app feel less like a generic catalogue and more like one that understands what each customer is trying to do. What you’ll be doing Lead and develop a high-performing team of around 12 Machine Learning Engineers, distributed across multiple pods and spread across London, Finland and Berlin, fostering a culture of technical excellence, ownership and rapid experimentation. Own and evolve the ranking, recommendation and personalisation systems across ordering surfaces, helping customers find the right items quickly as our selection grows. Set the technical vision for the team’s ML ecosystem, balancing near-term product goals with longer-term bets on areas like on areas across recommendations to agentic approaches, and intent-aware experiences that adapt dynamically to how customers browse and act. Lead the unification of our recommendation models across brands (Deliveroo, Wolt and DoorDash) and markets, working out how to power personalisation at global scale while keeping it feeling hyperlocal, and how to balance reusable core models against surface-specific adaptations without ending up with a sprawl of models. Partner with Product, Data Science and neighbouring engineering teams to identify high-impact opportunities, define roadmaps and translate ambiguous business problems into ML solutions. Provide technical guidance on modelling approaches, ML system design and production architecture, stepping in to challenge modelling decisions where needed without becoming a bottleneck. Drive key marketplace metrics such as conversion and engagement, balancing velocity and scope against sustainable, long-term technical quality. Stay close to the code so you understand how your team actually works, and help evolve the AI-assisted engineering practices and tooling that empower the team. What you’ll need to thrive Proven experience line-managing ML Engineers, ideally 6 or more direct reports, with a track record of building high-performing teams, coaching engineers through career progression and managing a horizontally distributed team across multiple pods or workstreams. Significant experience building and deploying machine learning systems in production at scale, in areas like Recommendations, Personalisation, Search, Ranking or Information Retrieval. Strong stakeholder management across product, engineering and business functions, with experience working across multiple teams and geographies. A pragmatic, impact-focused mindset, prioritising outcomes and customer experience over theoretical perfection. Why Join Us? At Deliveroo, you’ll do work that matters—solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community builders and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale - Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast - Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠 Grow through challenge and ownership - Take on big, ambiguous problems and accelerate your career with strong support. 🌎 A culture built for builders - High standards, collaboration, flexible working and continuous learning. ​​💰 Share in the success you help create - Competitive salary and equity options, so you’re rewarded for the impact you make. ➡️ Want a deeper look at how we build? Check out our Tech Blog . Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness .

Задачи: — Build RAG pipelines, semantic/vector search, conversational AI, and intelligent assistants. — Develop recommendation, ranking, classification, and predictive ML models. — Own end-to-end ML pipelines from data processing and training to deployment and monitoring. — Build MLOps / GenAIOps workflows, CI/CD, GPU inference, and cloud-native AI infrastructure. — Work with Product and Engineering to measure business impact through KPIs and experiments. — Improve AI system scalability, reliability, cost, governance, and performance. Требования: — 4–5+ years in AI, ML, or Data Science. — Strong Python, SQL, and production ML experience. — Hands-on experience with LLMs, Transformers, embeddings, RAG, and prompt engineering. — Experience with PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex. — Strong knowledge of Docker, Kubernetes, MLflow/W&B, CI/CD, AWS, and Terraform. — Experience with Kafka, ETL pipelines, vector databases, and search systems. — Ability to independently take AI projects from idea to production. Плюсом будет: — Experience with A/B testing, responsible AI, recommendation systems, regulated environments, or team leadership. — Candidate should be able to work on US time schedule. — Good English conversation skill is much much preferred.

Location: Warsaw Asana's Mobile Group builds the apps that keep millions of users connected to their work wherever they are. As the Engineering Group Lead for the Mobile Group in Warsaw, you will lead a team of 4 Engineering Managers and approximately 35 engineers who are responsible for Asana's iOS, Android, and Desktop apps. You will own the technical direction and execution of the Mobile Group and the growth of leaders on your team. You will also support Warsaw site strategy and operations as a member of senior leadership in Asana’s Warsaw office. 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 Lead, coach, and develop a team of Engineering Managers and their teams of approximately 35 engineers, owning hiring, performance, and career growth across the Mobile Group. Drive the delivery of high-quality mobile experiences across multiple products, holding accountability for code quality and customer experiences that ship to production. Develop, in partnership with Product and Design leaders, a multi-product mobile strategy built on top of shared platform investments. Own relationships across the organization, managing up and out to advocate for the Mobile Group, removing blockers, and creating clarity in a fast-moving environment where many workstreams run in parallel. Serve as a senior leader at the Warsaw site by flexing into operational, cultural, and cross-functional support roles as needed while helping grow other leaders in Warsaw. About you You have several years of experience managing people managers and being accountable for a sizable engineering organization (30+ engineers). You have recent, hands-on experience shipping mobile applications. You thrive in high-complexity environments and can balance competing priorities gracefully. You have a bias for ownership: you chase things down, build relationships across teams, and create forward motion. You are a fast and curious learner. The Mobile Group touches many different problem spaces and team contexts; you need to absorb new information quickly and apply it. You have a low ego. You are as comfortable diving into technical and product details as you are presenting strategy to executive leadership. You demonstrate curiosity about emerging technologies and a willingness to leverage them to enhance your team's productivity and decision-making. At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply. What we'll offer Generous, transparent and fair compensation system (base salary and RSUs) Contract of Employment (and the option of 50% tax deductible costs for author's rights usage in respect of applicable roles) Health insurance with dental and travel coverage (Lux Med) Breakfast and lunch catering on the days that you work from the office Career growth budget Home office setup budget Gym/Fitness card (MultiSport Plus) Mental Health Support through Modern Health (free therapy and coaching) Group life insurance MacBooks with all necessary accessories For this role, the estimated base salary range is between 54.000 - 64.000 PLN gross per month (subject to all taxes and necessary deductions). The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified. In addition to base salary, your compensation package may include additional components such as equity, and benefits. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role. #LI-Hybrid 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.

Задачи: — Build RAG pipelines, semantic/vector search, conversational AI, and intelligent assistants. — Develop recommendation, ranking, classification, and predictive ML models. — Own end-to-end ML pipelines from data processing and training to deployment and monitoring. — Build MLOps / GenAIOps workflows, CI/CD, GPU inference, and cloud-native AI infrastructure. — Work with Product and Engineering to measure business impact through KPIs and experiments. — Improve AI system scalability, reliability, cost, governance, and performance. Требования: — 4–5+ years in AI, ML, or Data Science. — Strong Python, SQL, and production ML experience. — Hands-on experience with LLMs, Transformers, embeddings, RAG, and prompt engineering. — Experience with PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex. — Strong knowledge of Docker, Kubernetes, MLflow/W&B, CI/CD, AWS, and Terraform. — Experience with Kafka, ETL pipelines, vector databases, and search systems. — Ability to independently take AI projects from idea to production. Плюсом будет: — Experience with A/B testing, responsible AI, recommendation systems, regulated environments, or team leadership. — Candidate should be able to work on US time schedule. — Good English conversation skill is much much preferred.