Разработка вакансии

Location: United States Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE The Senior Principal Software Engineer is responsible for shaping and evolving the company’s technical landscape. In addition to designing, developing, and maintaining core systems, the Senior Principal Software Engineer provides strategic guidance to align technology initiatives with business goals. This role is vital in ensuring that the platform is secure, scalable, and performant—capable of supporting rapid growth and driving innovation. _______________________________________________________________________ RESPONSIBILITIES TECHNICAL STRATEGY & ARCHITECTURE ● Define and drive the overarching technical vision, ensuring the platform meets current and future scalability, performance, and security needs ● Evaluate and select tools, frameworks, and architectures to maintain a state-of-the-art technology stack LEADERSHIP & MENTORSHIP ● Provide technical leadership and guidance to the engineering organization, setting best practices and standards. ● Coach and mentor engineers, fostering a culture of continuous learning and collaboration Innovation & Research ● Investigate emerging technologies, frameworks, and best practices ● Lead prototyping initiatives and proof-of-concepts that can transform the platform’s capabilities SCALABILITY & PERFORMANCE ● Ensure the platform is designed for high performance and can seamlessly handle increasing user loads ● Oversee performance optimization, load balancing, and capacity planning strategies RELIABILITY & AVAILABILITY ● Design fault-tolerant, highly available systems that minimize downtime and deliver a seamless user experience Infrastructure Automation ● Advocate for and implement Infrastructure as Code (IaC) principles, CI/CD pipelines, and automation best practices ● Continuously refine deployment, testing, and operations processes to improve efficiency SECURITY & COMPLIANCE ● Collaborate with security experts to ensure platform integrity, compliance with industry standards, and protection of sensitive data ● Proactively address security vulnerabilities and champion secure coding practices CROSS-FUNCTIONAL COLLABORATION ● Work closely with product managers, designers, and other stakeholders to ensure technical initiatives support business objectives ● Drive alignment between engineering roadmaps and product strategies TECHNICAL PROBLEM-SOLVING ● Tackle complex architectural and technical issues, providing clear direction and innovative solutions ● Serve as an escalation point for critical system challenges CODE QUALITY & REVIEWS ● Uphold coding standards through thorough code reviews, ensuring high-quality, maintainable codebases ● Establish and enforce best practices around testing, documentation, and version control DOCUMENTATION & KNOWLEDGE SHARING ● Produce comprehensive technical documentation, including architectural diagrams, design guidelines, and operational runbooks ● Promote a transparent engineering culture by sharing insights and successes across the organization _______________________________________________________________________ QUALIFICATIONS ● 12+ years of software engineering experience with demonstrated expertise across multiple domains (SDLC, AI engineering, corporate systems, etc) ● Extensive software engineering experience, with a track record in designing and implementing large-scale, distributed systems ● Deep technical expertise: Proficiency in multiple programming languages, cloud platforms (e.g., AWS, Azure, GCP), and modern development frameworks ● Leadership acumen: Demonstrated ability to lead diverse engineering teams, inspire innovation, and drive successful outcomes ● Architectural vision: Proven skill in defining and driving architectural roadmaps that align with evolving business needs. ● Problem-solving ability: Expertise in diagnosing complex system issues and designing robust, scalable solutions ● Communication skills: Excellent written and verbal communication skills, capable of influencing both technical and non-technical stakeholders. ● Security conscious: Solid understanding of security best practices, compliance standards, and data protection ● Continuous improvement mindset: Passion for optimizing processes, toolchains, and workflows ● Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience As a Senior Principal Software Engineer, you will not only architect innovative solutions but also shape the technical culture. Your leadership and expertise will be pivotal in building a resilient, cutting-edge platform that supports rapid growth and drives long-term success. Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs. _______________________________________________________________________   COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. United States: $219K – $352K base ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: New York City Office Workplace: OnSite COMPANY DESCRIPTION Today, when you go to your doctor and get referred to a specialist, your doctor sends out a referral and tells you, “They’ll be in touch soon.” So you wait. And wait. Sometimes days, weeks, or even months. Why? Because too often providers are overwhelmed with the painstakingly tedious work required to get paid by insurance companies. Powered by proprietary models, Tennr handles the complex paperwork that gets patients through the door and providers paid, helping operators get patients the right care, at the right time, in the right setting. ROLE DESCRIPTION We’re looking for a high-agency Senior Backend Engineer to bridge the gap between cutting-edge ML research and real-world product delivery. You’ll design and build agentic workflows that power complex healthcare processes to solve hairy infrastructure, workflow, and UX challenges in U.S. healthcare. This role involves creating data pipelines, evaluation harnesses, and scalable production-grade agentic systems. You’ll be responsible for researching the right tools and models, ensuring we always use the best-fit technology for each workflow.. As part of our ML team, you’ll work hand-in-hand with researchers to translate new techniques and insights into production-ready systems. The ideal candidate has full-stack engineering experience, hands-on expertise with LLM APIs, and a proven track record of deploying AI systems into production. You’ll work across the stack - from data collection to training pipelines to AI agent orchestration to frontend integration - bringing cutting-edge AI solutions to life in real-world healthcare environments. RESPONSIBILITIES As a Senior Backend Engineer on the ML team at Tennr, you’ll bridge the gap between cutting-edge ML research and real-world product delivery. You’ll help build agentic systems that use LLMs, and vision models, and structured automation to solve hairy infrastructure, workflow, and UX challenges in U.S. healthcare. - Ship full-stack AI systems end-to-end - Design resilient systems for model deployment, evaluation, and monitoring that stay reliable as traffic grows. - Go from ideation to code within hours; iterate quickly on experiments and data. - Collaborate with ML engineers, backend engineers, and cross-functional teams to integrate models cleanly with data pipelines and product QUALIFICATIONS - Proficiency in full-stack development, with a strong understanding of system design, backend engineering, and observability infrastructure. - A track record of working through the full lifecycle of building, testing, deploying, scaling, and monitoring LLM-centered software architectures. - Excellent communication and collaboration skills: aligning on interfaces, navigating tradeoffs, and driving cross-team execution. WHY TENNR? - Drive Impact: one of our company values is Cowboy, meaning you set the pace. You won’t just talk about things, you’ll get them done. And feel the impact. - Develop Operational Expertise: learn the inner workings of scaling systems, tools, and infrastructure - Innovate with Purpose: we’re not just doing this for fun (although we do have a lot of fun). At Tennr, you’ll join a high-caliber team maniacally focused on reducing patient delays across the U.S. healthcare system. - Build Relationships: collaborate and connect with like-minded, driven individuals in our Chelsea office 4 days/week - Free lunch! Plus a pantry full of snacks. BENEFITS - Beautiful new office at 345 Hudson Street - Unlimited PTO - 100% paid employee health benefit options - Employer-funded 401(k) match - Competitive parental leave

Задачи: — Развитие и кастомизация внутренних и внешних порталов на базе Bitrix — Разработка функциональных модулей для корпоративных порталов — Реализация интеграционных решений для обмена данными между информационными системами — Обеспечение стабильной работы бэкенда и интеграция с фронтендом на VueJS Требования: — Знакомство с платформой Bitrix / Bitrix24 (архитектура, инфоблоки, API, админ-панель) — Базовые знания PHP — Понимание работы баз данных и владение SQL — Понимание концепции REST API и взаимодействия клиента и сервера — Базовые знания HTML, CSS и JavaScript (jQuery, Ajax) — Владение Git, понимание принципов CI/CD — Знакомство с концепцией асинхронных шин данных и очередями сообщений Условия: — Неполный рабочий день — Возможна удалённая работа

Ищем Laravel-программистов.

Location: Budapest, Hungary About Wolt At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we’re building the delivery of (almost) everything and you’ll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe. Working at Wolt isn’t always easy, but it’s definitely exciting. Here you’ll learn more, build more, and ship more than in most other companies. You’ll be challenged a lot, but also have a lot of fun on the way. So, if you’re a self-starter with drive and entrepreneurial spirit, this could be the ride of your life. About the Team Wolt's Shared Service Center in Budapest is home to a team of 40 people who keep our operations running across markets. Ten of them focus on one mission: getting German merchants to live on Wolt quickly and correctly. They own the onboarding journey from the moment a partner signs to the day they start receiving orders. Now we're looking for someone to lead them. As Onboarding Team Lead, you'll be based in Budapest and work closely with our Onboarding Operations team in Germany, reporting to the Global Head of Business Process Outsourcing Management. You'll lead a team of 12 FTE, own the German onboarding pipeline, and make sure every partner gets a smooth, high-quality start on Wolt. The team is experienced and established, and it's ready for a leader who can raise the bar on speed, quality and process, while being its biggest advocate. What you’ll be doing You'll be responsible for how quickly and how well German merchants are onboarded onto Wolt. That means leading the people, owning the pipeline, and keeping a close eye on the numbers. You'll build a solid understanding of the full onboarding landscape, including POS integrations, gear workflows, commission changes and offboarding. You'll also be the go-to person when things get stuck. Day-to-day in this role you’ll: Lead, coach and develop a team of 12 FTE onboarding specialists, support them daily, and spot knowledge gaps and training needs. Own the onboarding pipeline so it always reflects reality. New venues are assigned the same day, follow-ups and on-hold reasons stay up to date, and stalled cases get escalated or offboarded instead of left open. Track the team's key onboarding KPIs, such as time to onboard and new live venues, so you always know where the team stands and can flag deviations early. Work with Sales, Account Management, Product and the Onboarding Operations team in Germany to escalate blockers early and improve how we onboard. Keep data quality high by validating issues yourself before escalating, sharing bug reports daily, and making sure partner information is accurate and complete. Plan team capacity ahead of holidays, business trips and short weeks so no partner is ever left without an owner. Our humble expectations You have at least 2 years of experience leading a team of 8 or more people, including setting clear performance expectations and following up on them. You have 3+ years of experience in operations in a fast-paced environment such as a marketplace, e-commerce or a shared service center. You're fluent in both German and English, written and spoken, because you'll work daily with German partners and stakeholders. You're comfortable working with data and use KPIs and dashboards to understand performance and make decisions. You're structured and detail-oriented, and you keep pipelines, timelines and data accurate without being chased. You take ownership, spot opportunities to improve processes, and drive changes independently. What we offer A key leadership role shaping how merchants in one of Wolt's biggest markets join the platform. A team that's already up and running, so you can focus on raising the bar rather than starting from scratch. Close collaboration with teams across Germany and Budapest, plus visibility across Sales, Account Management and Product. Career growth opportunities in a fast-growing company, backed by comprehensive internal training. Our Commitment to Diversity and Inclusion We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. Beware of recruitment scams: DoorDash, Deliveroo, and Wolt will never ask you to pay money or share sensitive financial information during hiring — learn more about our legitimate recruiting process at Recruitment Scam Awareness - DoorDash .

Задачи: - Разработка и поддержка пользовательских интерфейсов с помощью Vue 3 и TypeScript. - Проектирование и реализация адаптивной верстки для различных устройств. - Применение принципов ООП для написания чистого, масштабируемого кода. - Настройка и оптимизация сборки проектов с использованием webpack и Module Federation. - Работа с сетевым стеком: IP/TCP, HTTP/2, WebSocket. - Участие в архитектурном проектировании микрофронтендов. Требования: - Опыт коммерческой разработки от 3-х лет. - Уверенное владение HTML/CSS и адаптивной версткой. - Отличное знание TypeScript и понимание основных принципов ООП. - Практический опыт работы с Vue 3: написание и проектирование компонентов. - Понимание концепции Module Federation и микрофронтендов. - Знание сетевых протоколов: IP/TCP, HTTP/2, WebSocket. - Опыт работы с Git и понимание рабочих процессов командной разработки. Условия: - Полная занятость. - Гибкий график работы. - Официальное оформление по ТК РФ.

Develop and implement web applications and system enhancements. Take ownership of web projects from development to production.

Participate in the entire software development lifecycle; Collaborate closely with developers and CTO to deliver high-quality software solutions;

You will lead and execute core 0-to-1 initiatives in cutting-edge domains such as SaaS. You will translate high-level strategic vision into concrete execution roadmaps, driving rapid implementation from prototype to production.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is an unusually demanding distributed system. Training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts, exchange data continuously, and have to keep making progress while hardware fails, load shifts, and the research changes underneath them. How well that system holds together determines how much of our compute turns into learning, and how quickly the team can try the next idea. As a Research Engineer on the Distributed Systems team within RL Engineering, you'll work on whatever part of that system is the current limit. That might be scheduling and placement, data movement between components, running large numbers of sandboxed environments, storage and checkpointing, networking, fault tolerance, autoscaling, or the observability that tells us what a run is actually doing. We're looking for generalists: engineers who can move between these layers, reason from first principles about a system they haven't seen before, and pick the problem that matters most rather than the one closest to their prior experience. Our system changes as fast as the research does, correctness under failure matters as much as throughput, and the best solutions often come from understanding the ML workload well enough to know which guarantees it actually needs. Strong candidates have built and run large distributed systems, care about getting the details right, and want to apply that experience to a workload that is very large, very heterogeneous, and changing quickly. Key responsibilities Design, build, and operate the distributed systems that run RL at scale, across training, sampling, and environment execution Find and remove whatever currently limits the system, whether it's scheduling, data movement, storage, networking, or coordination Build fault tolerance into every layer: failure detection, isolation, and recovery that keep long-running jobs making progress without human intervention Design resource management and autoscaling so that compute follows demand as a run's needs shift Build observability that makes it possible to understand what a run is doing and why it slowed down, stalled, or produced unexpected results Build automation that detects and remediates common problems, and design interfaces that let engineers and automated tools operate runs safely Work with researchers and performance engineers to make sure systems changes preserve training correctness and don't introduce subtle nondeterminism Remove classes of failure at their source through incident review, testing, and redesign, and write clear design documents for what you build Minimum qualifications Strong software engineering skills in Python and at least one systems language such as Rust, C++, or Go Experience designing, building, and operating large-scale distributed systems in production Deep understanding of distributed systems fundamentals, including consistency, coordination, consensus, failure modes, and recovery Ability to reason quantitatively about throughput, latency, and resource costs across compute, memory, storage, and network Experience debugging complex failures across many hosts and services, including failures you can't reproduce locally Strong written communication, including design documents and incident writeups Preferred qualifications Experience running ML training or inference infrastructure at scale Experience across several layers of the stack, such as scheduling, storage, networking, and orchestration Experience building schedulers, autoscalers, or resource management systems Experience with container orchestration such as Kubernetes, and with sandboxed or virtualized code execution at scale Experience with high-performance networking, RDMA, or collective communication libraries Experience building observability or automated remediation for large fleets Experience with async Python frameworks such as Trio or asyncio Familiarity with reinforcement learning or large language model training workloads Representative projects Design a scheduler that places training, sampling, and environment work across a heterogeneous cluster while respecting network topology and failure domains Build a failure detection and recovery system that lets a long-running job survive host and network failures with minimal lost work Scale environment execution substantially without increasing tail latency for the training step Design an autoscaling policy that rebalances compute across components as a run's bottleneck shifts Build a diagnostics system that explains why a run's throughput dropped and proposes a fix Trace a rare data corruption bug across many services to a race condition in a recovery path, and redesign the path so the class of bug can't recur Design the operational interface for a run so that automated tools can safely diagnose and adjust it under human oversight The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Задачи: — Проектирование и разработка backend-сервисов на Go — Участие в проектировании архитектуры систем и принятии технических решений — Разработка и поддержка API (REST/gRPC) и интеграций с внешними сервисами — Оптимизация производительности и надежности высоконагруженных сервисов — Работа с базами данных и очередями сообщений — Код-ревью, менторинг middle-разработчиков, участие в формировании стандартов разработки Требования: — Коммерческий опыт разработки на Go от 4 лет — Глубокое понимание конкурентности в Go (goroutines, channels, context) — Опыт проектирования микросервисной архитектуры — Уверенная работа с PostgreSQL, понимание индексов и оптимизации запросов — Опыт работы с брокерами сообщений (Kafka/RabbitMQ/NATS) — Опыт работы с Docker, Kubernetes, CI/CD — Опыт написания тестов (unit, интеграционные) Будет плюсом: — Опыт работы с ClickHouse / Redis — Опыт настройки мониторинга (Prometheus, Grafana) — Опыт интеграции LLM/ИИ-сервисов в backend — Опыт работы в аутсорс/аутстафф формате Условия: — Полная занятость (fulltime), удаленный формат работы — Заработная плата от 350 000 ₽ в месяц — Участие в технологических ИИ-проектах — Прямая коммуникация с техническим руководством без бюрократии — Реальное влияние на архитектуру и технические решения

Требования: — 3+ года профессионального опыта в роли Backend Developer. — Уверенное владение Java и Spring Framework. — Владение SQL и проектированием реляционных баз данных. — Опыт работы с NoSQL базами данных, например Redis. — Хорошее знание английского языка. Условия: — Поддержка релокации. — Полная занятость. — Конкурентная заработная плата. — Работа в офисе в Лимассоле. Задачи в описании не указаны.

Location: San Francisco, CA Senior Software Design Lead, IDEO San Francisco In a nutshell: IDEO San Francisco is in search of a Senior Software Design Lead who will architect the human and technical systems behind the digital products and AI experiences we design, build prototypes that behave like real production software, and be the technical voice client CTOs trust. You'll pick up design at IDEO along the way. Why is this role important for IDEO’s work? Software design makes the biggest impact by turning a product vision into something a client can actually build, and by testing ideas in working code rather than static screens. Their skillset is critical to our business because the work has evolved from designing interfaces to designing systems: how people, software, and AI agents behave together. We count on them to understand data models, APIs and agentic infrastructure from first principles, and speak credibly on technical choices with executives and engineering leaders. Once here you will: Work with product designers, product strategists and design researchers on 8–12+ week digital product engagements that may span from product vision and strategy to full end-to-end build. You will play a key role in turning human insights into technical architecture: data, APIs, integrations and the agentic layer. Build early prototypes with real data, real models and real integrations, so we learn quickly and lower the risk of big bets. Advise client executives and engineering teams on tech stack choices, build-vs-buy, evaluating APIs and LLMs, and feasibility. Design how agents and systems behave on a human's behalf, including guardrails, failure states and how the system stays legible to both people and machines. Raise the craft bar inside IDEO. Create reusable starter kits and toolkits so teams stop building from scratch, and coach designers who prototype in code. Help shape proposals and scope technical work in business development. What does IDEO offer you? IDEO is a place where you can solve diverse, complex challenges for our clients and their organizations, alongside thoughtful, intelligent individuals who lead with curiosity, empathy, and humility. We intentionally craft moments that allow our community to pause, create, and connect. We encourage our community to bring their whole selves to work, respect the need for work-life balance, and allow for autonomy in the design process and your career. As a Software Designer in San Francisco, we provide the opportunity for you to: Learn design from a leading design and innovation firm . IDEO's founders designed Apple's first mouse and the first laptop. Since then, we've kept people at the center of design through every wave of technological change. You'd learn to do field research with real people, synthesize insights and tell compelling stories, and work alongside some of the best designers in the world. Work across many problem spaces . In one year you might redesign a retail or finance app, prototype new ideas in media and entertainment, and take on systemic challenges in health and education. Working across clients and industries stretches your thinking. A good solution isn't only technically sound: it has to fit real people, real businesses and the constraints they work within. Be in the room for the "why" before the "how." You'd shape the question from day one instead of receiving a spec after decisions have been made. And you’d help build this practice at IDEO to shape how next generation digital products are designed and built in the era of AI. Some previous projects to check out: Straight Arrow News : a redesigned news app and website with features like See All Sides, Sources and Media Landscape views. App page views grew 1,170% and active users 700%. This role would design the content and data model underneath and prototype with real feeds. Gates Foundation – Last Mile Money : human-centered design for 100+ digital financial products serving 34M underserved users. This role would work on architecture for low-connectivity settings and evaluate partner platforms and APIs. Jack Technology – Aitu : AI-enabled industrial sewing machines and a humanoid robot, designed around how they work with factory workers. This role would work on system behavior: how the AI signals what it's doing and how humans stay in control. Relevant experience and mindset: Must-haves: 6-8+ years as a software engineer shipping production software, ideally at growth-stage or established tech companies where speed and scale both mattered. You've taken products from concept to launch. 1-2+ years as an engineering lead or solutions architect: scoping, estimating and planning projects, and making architecture decisions others build on. You think at a systems level. Deep software fundamentals, including systems design, data modeling, APIs, and tradeoffs around performance, security and scale, plus fluency in a modern stack (e.g., TypeScript, React, Python, Node; AWS, GCP, Azure). Hands-on building with LLMs (tool use, agents, retrieval, evals) and advanced prototyping. You turn concepts into working software quickly, using real data and integrations, with quality that holds up beyond vibe coding. A track record of working closely with product, design and data, plus curiosity about people and a desire to learn how the craft of software intersects with product and design. You use prototypes as a way to think, not just to deliver. Strong communication and storytelling: architecture diagrams, system maps and presentations that make technical recommendations clear and persuasive to executives and engineering leaders. Nice-to-haves: Comfort with Figma, design systems and front-end craft Client-facing or consulting experience, or taking part in UX research Experience with hardware or connected devices (Arduino, IoT) Pop quiz, Hot Shot: A client's CEO wants "an AI agent in the app by Q2." What's your first question for the CEO? What's a piece of software that's beautifully built under the hood, not just on the surface? What makes it good? Application requirements and instructions: Résumé, LinkedIn + Cover Letter (Optional) GitHub or two to three work samples (code, architecture docs, side projects or technical writing) A short response of about 300 words: "Tell us about a technical decision you made that shaped how people experienced a product. What were the tradeoffs, and what would you do differently today?” Payscale & Benefits IDEO is committed to paying its employees, contractors & vendors equitably, regardless of gender identity or race/ethnicity/cultural identity. The salary range for this role is $130,000-150,000 USD. Final offers may vary based on candidate experience, location, and other factors. As a full-time position, this role is eligible for employee benefits. In addition to base compensation, IDEO offers a rich benefits package including the following: Hybrid Model: Team members based in the San Francisco Bay Area are expected to work in the studio on Tuesdays, Wednesdays, and Thursdays, with flexibility based on client travel, project needs, and deliverables. Candidates based outside the Bay Area are not expected to be in the studio regularly, but should be available to travel as needed for IDEO and client work. Health Benefits: Vision, Dental, Healthcare Financial Benefits: 401K with Employer Contribution Family & Caregiving: Parental Leave, Adoption Assistance, Fertility Assistance, Transgender Medical Assistance, Breastmilk shipment, Back-up/Dependent Care, Pet Insurance Other Benefits: Flexible Work, Flexible Time Off, Paid Holidays, Annual Education Stipend, Home Office Stipend, Commuter Reimbursement, and Phone & Internet Reimbursement Commitment to Diversity At IDEO, we are committed to the work of advancing diversity, equity and inclusion within our organization and in the world. Our purpose of having disproportionate, world-changing impact through design is directly connected to our ability to bring many different perspectives to the table. This applies to our candidates, the people we hire, the clients and customers we serve, and the communities we learn from in our research. Please note that the successful candidate must be based in the United States and have the unrestricted right to work in the US. Unfortunately, we are unable to offer sponsorship for this role. IDEO proudly supports flexible work.

Разрабатывать и поддерживать бекенд сервисы на Python. Участвовать в разработке архитектуры и концепции продукта.

Обязанности Разрабатывать микросервисы на Go; Проектировать архитектуру новых микросервисов;

SQLAlchemy Тестирование: pytest — обязательное; построение пирамиды тестирования, интеграционные тесты Управление зависимостями: pip / poetry / uv Знание принципов и архитектуры web-сервисов и REST API Проектирование микросервисных решений Уверенная работа с Docker (включая docker-compose);

Location: San Francisco, CA Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Real-World Test Lab (RWTL) Physical AI doesn't get graded on a leaderboard. It gets graded on a factory floor at shift change, in a substation with no GPS, on a site where the lighting is wrong and the stakes are real. The Real-World Test Lab closes the gap between the benchmark and the field. We bring the customer's world inside our walls — their devices, their environments, their hardest conditions, and their definition of success — and make it the bar every release has to clear. As Niantic Spatial's first and most demanding customer, we push our reconstruction, localization, and spatial understanding to their limits, find where they shine and where they break, and turn that into evidence that shapes what we build next. It's a new team at the frontier of physical AI, and you'll help invent how the job is done. About the Role We're hiring a Hardware Operations Engineer with a robotics specialism, reporting to the Director of the Real-World Test Lab, to own the physical layer of our evidence. You'll manage our fleet of capture devices and robots, engineer the test environments and the instrumentation inside them, support the captures our data programs depend on, and run physical test sessions, including the real-robot side of our sim-to-real work. A physical run only counts as evidence if the hardware is characterized, the environment is controlled, the ground truth is trustworthy, and someone can reproduce the run months later. You'll build what makes that possible: fixtures, ground-truth references, calibration and data-offload tooling, and the integrations that feed physical runs into the same automated evaluation system as everything else. You engineer the conditions, not just the setup. When a physical result didn't match expectations, you've worked out whether the hardware, calibration, environment, or system under test was responsible. Then you built the rig, reference, or logging that kept the question from coming back. You know an uninstrumented physical test is an anecdote, and in the Lab you'll be the person who can say with authority whether a strange result is real. What Success Looks Like - 30 days: Fleet inventory and characterization baseline complete, safe operating procedures defined for current spaces, and first instrumentation gaps identified. - 60 days: First physical robot run executed with ground-truth instrumentation, documented well enough to repeat, with results in the Lab's evaluation system. - 90 days: Test environments in regular use with controlled, documented conditions; capture support running smoothly with our data acquisition team; and the physical side of sim-to-real running on a standing instrumented protocol. What You'll Do - Own and Characterize the Fleet - Manage our capture devices, sensors, and robots end to end: inventory, calibration, firmware, maintenance, logistics, and spares. Characterize what each platform can and cannot do, so a device's limits are a known quantity rather than a surprise inside a result. - Engineer the Physical Test Environments - Design, build, and operate the spaces we test in, covering layout, lighting control, markers, obstacle configurations, and survey-grade ground truth references, across our office, rented or workplace-services-supported space, and partner or customer sites. Make each environment a controlled variable rather than an improvisation. - Build the Instrumentation - Create the rigs, mounts, references, and measurement setups that turn a physical run into quantitative data: trajectory ground truth, positional accuracy references, timing and synchronization across sensors, and automated condition logging. - Integrate Physical Runs Into the Evaluation System - Work with the AI Automation Engineer so physical results flow into the same scorecards and comparisons as software-only evaluations, through automated data offload, run metadata, and structured condition capture rather than a spreadsheet and a folder of files. - Run the Physical Test Sessions - Execute robot runs and device-in-the-loop tests: robot bring-up, teleoperation, scripted trials, and the repetition that makes a result statistically meaningful rather than anecdotal. - Own the Physical Half of Sim-to-Real - When a scenario has been evaluated in simulation, engineer and execute its physical counterpart so the comparison is valid, matching environment, route, lighting, sensor configuration, and robot setup, and instrumenting the run so divergence is explainable rather than mysterious. - Own Safety - Define and maintain safe operating procedures for robots and powered equipment in our test spaces, and coordinate with workplace services, IT, Legal, and site owners on access and safety requirements. - Automate Your Own Work - Script the repetitive parts, including configuration, calibration checks, data offload, and condition logging, so setup time falls and a colleague can run a session without you. What You'll Bring - Hands-on engineering experience with robotic hardware, covering bring-up, integration, teleoperation, troubleshooting, and maintenance. Mobile or wheeled platforms preferred. - Built test rigs, fixtures, or instrumentation that produced quantitative measurements of a physical system's behavior. - Designed and run structured physical experiments, including ground truth methodology, and documented conditions rigorously enough for someone else to reproduce them. - Worked with sensor calibration, multi-sensor synchronization, and coordinate frame conventions, and understand how errors in each propagate into a result. - Strong Python and command-line proficiency, with a track record of automating hardware configuration, data offload, or test execution. - Managed hardware fleets operationally: inventory, firmware, calibration schedules, logistics, and repair coordination. - Practical safety experience operating powered equipment or robots around people. - A bachelor's degree in a relevant field, or equivalent experience. Nice to Have - Worked with ROS or ROS 2, including writing nodes or integrating sensor drivers. - Operated NVIDIA Isaac Sim or Isaac Lab as a user, running scenarios someone else authored. - Worked with professional capture hardware such as terrestrial laser scanners, NavVis or Leica systems, LiDAR, 360 cameras, or drones. - Established survey-grade or motion-capture ground truth for localization or navigation evaluation. - Supported photogrammetry, Gaussian splat, or 3D reconstruction capture workflows. - Run test operations at customer or partner sites, with the coordination and discretion that requires. Competencies - Engineering judgment about physical systems. You reason about error sources: calibration drift, timing offsets, mounting rigidity, lighting variation, floor surface. When results disagree, you form a hypothesis and design the measurement that settles it. - Hands-on and unfazed. You'd rather be in the space with the robot than reading about it. Cables, mounts, batteries, firmware, and a session that starts at 7am are all part of the job. - Meticulous about conditions. You instrument rather than remember. You know the value of a physical test lives in how precisely its conditions were captured. - Safety-minded without being slow. You take real responsibility for operating robots around people, and you build procedures where the safe path is also the fast path. - Builds for other people. Your fixtures, scripts, and procedures get used by colleagues without you in the room. - Comfortable in an unfinished environment. Much of this does not exist yet. You'll be selecting equipment, designing the first rigs, and defining how a space gets configured, with support but without a playbook. Compensation & Benefits Base salary range of $142,200 to $193,000. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

Location: San Francisco, CA Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Real-World Test Lab Physical AI doesn't get graded on a leaderboard. It gets graded on a factory floor at shift change, in a substation with no GPS, on a site where the lighting is wrong and the stakes are real. The Real-World Test Lab closes the gap between the benchmark and the field. We bring the customer's world inside our walls - their devices, their environments, their hardest conditions, and their definition of success - and make it the bar every release has to clear. As Niantic Spatial's first and most demanding customer, we push our reconstruction, localization, and spatial understanding to their limits, find where they shine and where they break, and turn that into evidence that shapes what we build next. It's a new team at the frontier of physical AI, and you'll help invent how the job is done. About the Role We're hiring an AI Automation Engineer, reporting to the Director of the Real-World Test Lab, to build the system that produces our evidence. Today our evaluations are manual, inconsistent, and slow. You'll design and own the automation that runs them end to end on every relevant release, with no human driving it, turning one-off experiments into an always-on service the whole company relies on. This role is about owning the evidence, not executing a test plan. You'll decide how each workflow gets exercised, and you'll be measured on whether the company can trust the results, not on how much automation exists. The work counts when it keeps running correctly months later, without you in the loop. You believe evaluation is engineering, not process. You've built systems that test other systems, and you know the difference between a script that works on your laptop and infrastructure a team can trust. When a result couldn't be reproduced, you fixed the tooling instead of arguing about the number. What You'll Do - Build the Evaluation Machine - Own the automation that executes Lab evaluations end to end: environment setup, run orchestration, artifact capture, and result collection. Make reruns free so we test constantly rather than occasionally. - Make Results Comparable - Instrument scorecards so a result can be compared across product versions, devices, and capture conditions. A number without its lineage is not evidence. - Automate the Agent-Driven Layer - Build the agent workflows that exercise priority customer use cases at realistic scale, across the graded difficulty spectrum from easy to frontier, and be honest about where agents cannot yet replace human judgment. - Kill Manual Work Permanently - Convert one-off experiments into standing protocols that run on every relevant release. Automate recurring inspection wherever it can be automated, and route what genuinely cannot to scalable human review. - Make Failures Actionable - Produce diagnostics precise enough that a finding reaches its owner with a reproducible case and data attached. Findings that need re-investigation before anyone can act on them are half-finished. - Keep Data From Being the Bottleneck - Work with the AI Data Manager so every run is reproducible from a known dataset state, without anyone downloading and re-uploading data by hand. What Success Looks Like - 30 days: One priority workflow evaluated end to end with no manual steps, with results in a comparable scorecard. - 60 days: Evaluations trigger automatically on relevant releases, with diagnostics that route failures to the right owners. - 90 days: Three priority workflows under standing automated evaluation, with version-over-version comparison for leadership. What You'll Bring - Built and maintained production-grade automation or test infrastructure that other engineers relied on daily. - Experience evaluating systems where correctness is graded rather than binary, meaning quality, accuracy, or latency thresholds rather than pass/fail assertions. - Strong Python, with fluency in orchestration, CI-style pipelines, cloud storage, and reproducible environments. - Worked with backend services and APIs you did not own, integrating against them without becoming a bottleneck for their team. - Written up a technical finding clearly enough that a non-author could act on it without a meeting. - A bachelor's degree in a relevant field, or equivalent experience. Nice to Have - Built agent-based or LLM-driven automation for a task that previously required human judgment. - Worked on evaluation or benchmarking for computer vision, 3D reconstruction, or spatial systems. - Instrumented dashboards or scorecards that leadership used for release decisions. - Operated data provisioning or registry infrastructure across multiple environments and access models. Competencies - Intellectually honest. You design tests that produce answers people can trust, and you refuse to let a benchmark imply more than the evidence supports — including when the honest answer is inconvenient for your own work. - Pragmatic. You find the fastest path to a defensible result without going through one-way doors that undermine scaling. You have no patience for building infrastructure nobody has asked for yet. - AI-forward by instinct. You reach for agents and LLM-driven automation before you reach for headcount, and you're rigorous about verifying what they produce. - Builds for other people. You've maintained something after the initial excitement wore off. Your tooling is documented, your failures are legible, and colleagues use what you build without asking you to run it for them. Compensation & Benefits Base salary range of $158,400 to $210,000 per year. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.