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Location: San Francisco, CA Workplace: Hybrid About Niantic Spatial We are building for the >80% of economic activity that happens beyond the reach of screens. AI has learned from the text, images and video online, but it still lacks an accurate understanding of physical space. 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.

Задачи: — Управление командой из 4–6 разработчиков и ML-инженеров, влияние на стратегию развития симулятора. — Совершенствование модели движения автомобиля, включая имитацию экстремальных ситуаций (порывы ветра, прокол колеса) и физику столкновений. — Построение и внедрение модели имитации восприятия автомобиля, имитирующей работу моделей детекции при различных погодных условиях, освещённости и дорожных ситуациях. — Кросс-функциональная работа: систематизация и приоритизация заказов от других команд, управление ожиданиями по точности системы и внедрению новых функций. Требования: — Опыт управления командой бэкенд- или ML-разработчиков. — Опыт внедрения моделей машинного обучения в продакшен и готовность разбираться в новых архитектурах и областях. — Готовность работать руками на этапе прототипирования и проверки гипотез. Будет плюсом: — Опыт работы с симуляторами или робототехническими платформами (ROS, Gazebo, CARLA, NVIDIA Isaac Sim и др.). — Участие в соревнованиях по ML или программированию (ACM ICPC, Codeforces, TopСoder, Kaggle и т. д.). — Знание правил дорожного движения, опыт вождения автомобиля или мотоцикла. Условия: — В крупных офисах есть спортзалы с тренажёрами, инвентарём и душевыми. — Полный список бонусов доступен на сайте компании.

Location: München, Germany; Berlin, Germany Workplace: Hybrid WHY THIS ROLE IS EXCITING Rohlik is the leading Central European e-grocer. More than a million customers buy their groceries from us through Rohlik.cz http://Rohlik.cz, Knuspr.de http://Knuspr.de, Kifli.hu http://Kifli.hu, Gurkerl.at http://Gurkerl.at and Sezamo.ro http://Sezamo.ro, choosing from over 17,000 items, delivered within a couple of hours in 15-minute windows. We are building the autonomous grocer. Maia, our AI assistant, already talks to customers and builds their orders; agents are moving into our buying and logistics; vision models are learning to watch quality. The next frontier is physical: robots taking over more and more of the work in our fulfilment centres, until fresh food moves from producers to households at a cost nobody else can match. We are setting out to record how our own people handle groceries and to turn those recordings into a training corpus for manipulation policies. Our warehouses already log what happened on every pick and every quality check, so the recordings can carry labels most datasets never get. Making that hold is part of the job. You decide what makes an hour of footage trainable — before we bank hundreds of them. WHAT YOU WILL OWN AND DELIVER - The capture spec. Cameras, mounts, calibration, and what disqualifies an episode. You write it before we buy the fleet and enforce it after. When the spec and the floor disagree, you go to the floor and find out which one is wrong. - Ground truth. Hand pose is the signal that transfers from human video to robot policies, and warehouse reality — work gloves, occlusion, cold halls — is exactly where the published models struggle. You own how we measure that and how we close the gap. - The evaluation harness. The corpus only counts if a policy can train on it. You build the harness that decides which hours make the bank, and you hold the trainability bar as the volume grows. - The first training runs. Once hours bank, you post-train open robot-learning models on our data and run the first task evaluations. - Judgment before spend. The field moves monthly. You read what is published, reproduce the claims we depend on, and steer our capture before the money is spent, not after. THE SCOPE This is a seat on a small, newly created team: an operations lead who runs capture on the floor, a data engineer who owns the pipeline, and you: the machine-learning voice in the room. This is not a research-scientist role, and no publication record is required. The job is to make a corpus trainable and to train the first policies on it. WHAT WE ARE LOOKING FOR - 3+ years of relevant full-time robotics experience. - PyTorch, and computer vision with real 3D geometry. Camera calibration, pose estimation, SLAM fundamentals. You have debugged an extrinsic calibration at least once in your life and know why it drifted. - You can read a paper and reproduce it. Our pipeline is assembled from published work, and your job is knowing which claims survive contact with a chilled warehouse hall. - You know what policies train on. Familiar with the current robot-learning stack and policy classes well enough to know what the training side will demand of the data before the data exists. - Dataset instincts. You have trained on data you collected yourself, and you know the failure modes that only show up at training tim.. - Comfortable as the only ML voice. You make the call, write it down, and revisit it when the pilot data says otherwise. - AI is how work gets done here. Our engineers use Claude Code and Devin daily, and we expect you to direct agents for the unglamorous parts — harness code, data plumbing, reproduction scripts — while keeping the quality bar exactly where it was. - Particularly relevant. Hand-pose estimation or egocentric video in production; multi-camera rigs and time sync; experience post-training robot-learning models; ROS 2. WHAT SUCCESS LOOKS LIKE IN 90 DAYS You have written the capture spec and we set up the first rigs against it. Your pilot gates have numbers, the first hours have passed your harness, and you can tell the people who sign the budget, with data, what the next hundred hours should look like. ARE WE A GOOD FIT? Take this role if you would rather own the spec that decides whether a dataset becomes an asset or a write-off than tune someone else's model on someone else's data, if a fulfilment centre at 6 a.m. sounds like a lab to you, and if you want the shortest possible line between your technical judgment and a capital decision. Read our culture code https://career.rohlik.group/group/our-culture-code and are we a good fit? https://career.rohlik.group/group/are-we-a-good-fit. WHAT WE OFFER - The physical-AI side of the autonomous grocer, with the capture spec and the first training runs yours from day one - A data asset few teams in the world get to build, in fresh groceries, a domain as hard as manipulation gets - Off-the-shelf hardware, a managed cloud estate, and a mandate that has already started - Benefits — see what we https://career.rohlik.group/group/what-we-offeroffer https://career.rohlik.group/knuspr/unser-angebot ARE YOU IN? Instead of a cover letter: pick a published human-video-to-robot-policy pipeline you rate, and tell us where it breaks on a warehouse floor where every hand wears a work glove. #LI-ML1 #Knuspr

Neoai IT Center izlayapti mutaxassislarni bir nechta yo'nalishlarda: backend dasturlash (python, Django, Fastapi, Node.js, Express.js, Java, Spring Boot, PHP, Laravel, Rest API, Postgresql, Mysql, Mongodb, Git, Docker), frontend (HTML, CSS, JavaScript, TypeScript, React, Next.js, Vue.js, Angular, Tailwind CSS, Bootstrap, Git), mobil dasturlash (Dart, Flutter, Kotlin, Java, Swift, React Native, Firebase, Android Studio, Xcode, Git), UX/UI dizayn (Figma, Adobe XD, Photoshop, Illustrator, Figjam, UI Design, UX Research, Wireframing, Prototyping, Design System), kiberxavfsizlik (Linux, Python, Bash, Networking, TCP/IP, Wireshark, Nmap, Burp Suite, Metasploit, OWASP, Git, Docker), data science (Python, Numpy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow, PyTorch, SQL, Jupyter Notebook, Git), data analitika (Python, Pandas, Numpy, SQL, Excel, Power BI, Tableau, Matplotlib, Seaborn, Jupyter Notebook), sun'iy intellekt (Python, PyTorch, TensorFlow, Keras, Scikit-learn, Hugging Face, OpenAI API, Langchain, Numpy, Pandas, Git, Docker), robototexnika (Python, C++, Arduino, ESP32, Raspberry Pi, ROS, Matlab, Arduino IDE, OpenCV, Sensors, Git). Ish joyi Toshkent shahrida, ish vaqti 3 soat, maosh 4-5 million so'm. Vazifalar: o'quvchilarga zamonaviy IT texnologiyalarini nazariya va amaliyot asosida o'rgatish, darslarni amaliy loyihalar va real vazifalar bilan tashkil etish, o'quvchilar bilan individual ishlash va ularning rivojlanishini kuzatib borish, dars materiallari va amaliy topshiriqlar tayyorlash. Nomzodlar mas'uliyatli, kommunikativ bo'lishi, o'z yo'nalishi bo'yicha amaliy tajribaga ega bo'lishi, yangi texnologiyalarni muntazam o'rganib borishi talab etiladi. Shuningdek, tajribali mutaxassislar bilan birga professional muhitda rivojlanish imkoniyati mavjud.

Location: Москва Команда центра аэрологистики, которая входит в состав департамента автономных решений, занимается научными исследованиями в области построения логистических маршрутов с применением отечественных моделей беспилотников и отдельных технологических решений. Научные достижения и технологические разработки в этом направлении открывают широкие перспективы для дальнейшего повышения конкурентоспособности отрасли. Обязанности * Определять архитектуру системы автопилота и входящих подсистем * проектировать ПО компьютера-компаньона: границы подсистем, интерфейсы, потоки данных, модели состояний и жизненный цикл компонентов * выстраивать взаимодействие с PX4/ArduPilot: выбирать протоколы и интерфейсы, определять контракты команд и телеметрии, обрабатывать потерю связи и отказы * выбирать и обосновывать middleware: ROS 2, DDS, QoS, executors, lifecycle nodes — или альтернативные решения, когда они действительно оправданы * проектировать работу в реальном времени: бюджеты задержек, частоты обновления, синхронизацию времени и управление нагрузкой * разрабатывать ключевые компоненты на Python/C++ и доводить их от прототипа до production-кода * проводить code review, принимать архитектурные решения, декомпозировать задачи и развивать инженерные стандарты команды. Требования * Глубокое знание современного C++17/20: RAII, управление памятью, concurrency, синхронизация потоков, обработка ошибок, проектирование API, профилирование и отладка * сильный опыт production-разработки на Python: прототипирование, тестирование, симуляция, автоматизация и анализ логов * уверенное понимание ROS 2: DDS, QoS, executors, callback groups, lifecycle, composition, intra-process communication, TF2, rosbag и диагностика распределенного графа * знание робототехники: системы координат и преобразования, кинематика, EKF/UKF, sensor fusion, наблюдаемость, ошибки навигации, основы траекторного планирования и динамики БПЛА * понимание архитектуры PX4 и/или ArduPilot: внутренние интерфейсы, оценивание состояния, режимы полета, offboard/external control, failsafe и интеграционные границы * рабочие знания Embedded и Linux: процессы и потоки, IPC, systemd, сеть, драйверы, real-time Linux, приоритеты планирования и диагностика проблем ядра * умение разбивать сложную систему на понятные компоненты, задавать требования к задержкам и синхронизации, находить баланс между надежностью, производительностью и сроками. **Будет плюсом:** * Опыт проектирования автономных робототехнических или беспилотных систем * практика интеграции камеры, лидара, IMU и GNSS в единую систему восприятия и навигации * опыт работы с MAVLink, uXRCE-DDS, Zenoh или другими интерфейсами взаимодействия с полетным стеком * опыт настройки и диагностики real-time Linux на embedded-платформах * опыт построения тестовой стратегии: симуляция, HIL, стендовые испытания, регрессионное тестирование * опыт технического лидерства небольшой инженерной команды * навыки работы с генеративными AI-моделями; опыт создания AI-агентов и использования их в работе будет преимуществом * опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки создания и использования AI-агентов * инструментальное владение AI для анализа, генерации и автоматизации. Условия * Комфортный офис в Сколтехе * офисный формат работы * конкурентная компенсация (оклад и премии по результатам деятельности) * ДМС c первого рабочего дня, страхование от несчастных случаев и тяжелых заболеваний * материальная помощь и социальная поддержка, корпоративная пенсионная программа * дисконт-программы от компаний партнеров * бесплатный фитнес на территории работодателя * подписка Прайм с возможностью совместного использования на трёх близких * внешнее и внутреннее профессиональное обучение: семинары, тренинги, конференции, корпоративная библиотека.

Location: Santa Clara, CA Workplace: onsite Role Overview We are looking for a Senior Software Engineer to own the systems that power a large-scale data collection operation, including the collection platform, operator tooling, data pipeline, and fleet infrastructure. This is an engineering role. Day-to-day teleoperation is performed by a dedicated operator team that you direct — you build what they run on, and you own what comes out of it. Project Details Location: 100% Onsite (Santa Clara, CA, US) Employment: Full-time W-2, Monday–Friday, 9:00 AM–5:00 PM Start Date: ASAP Contract Duration: 12-month contract with possibility of extension Rate: $105/hour What You’ll Do Design, build, and maintain the software behind our data collection stations — teleoperation stack, multi-camera recording, and session tooling. Deploy and upgrade that stack across the fleet without stopping collection; keep workstations, containers, and networking healthy. Own the data pipeline end to end: automated validation, conversion into our dataset format, upload, metadata, and versioning. Build the QA tooling that catches dropped frames, stream desync, bad calibration, and mislabeled episodes before data reaches training. Direct a team of teleoperators — define task protocols and SOPs, onboard them on new tasks and embodiments, review session quality, and unblock them daily. Own fleet reliability: calibration and firmware pipelines, sensor and end-effector integration, root-cause analysis of recurring faults, and vendor escalation. Bring up new stations and new embodiments; report throughput, yield, and data health to the research team. What we need to see MS in CS, Robotics, EE/ME, or a related field (or BS with equivalent hands-on experience). 3+ years building software for real robot systems — not simulation only. A system you designed and shipped that other people depended on daily, and that you kept running. Strong Python and Linux; Docker, git, CI, and SSH-based fleet administration. Robot middleware and real-time multi-sensor recording — ROS 2 or equivalent vendor SDKs. Experience supporting a data collection or teleoperation operation: you have built the tools operators depend on and owned throughput and quality numbers. Comfortable around robot hardware — arms or humanoids, dexterous hands, RGB-D cameras, and the calibration that keeps them honest. Able to lead operators without formal authority: you write clear SOPs, train people, and communicate status without being asked. Ways to stand out from the crowd Humanoid or bimanual platforms (Unitree, Fourier, ALOHA/ARX-class rigs) and dexterous hands. XR teleoperation: Quest / PICO / Vision Pro, motion-capture gloves, whole-body retargeting. Imitation-learning data tooling — LeRobot, HDF5/Zarr episode stores, dataset versioning, S3 at TB–PB scale. Built internal dashboards or tooling for a production line or high-throughput lab. Open-source contributions to robotics data or teleoperation tooling. #L1-CC1 Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.   To know more details (Click here)   In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.  In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program.     As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com   To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

Location: Remote-Friendly, United States 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 Anthropic is bringing data center capacity online faster than the industry has ever attempted, and the owner-furnished equipment (OFE) that makes a site live — switchgear, transformers, UPS, generators, busway, PDUs, chillers, CDUs, air handlers, dry coolers, pumps and piping skids — is long-lead, high-value, and sits squarely on the construction critical path. When a transformer slips three weeks at the factory, a data hall slips three weeks at the site. We're hiring a Supply Chain Delivery Manager to own that equipment from purchase order to dock. You will be the site-facing supply chain lead for a regional portfolio of data center projects: tracking every OFE line item against the construction schedule, running factory and logistics escalations with OEMs, holding suppliers and general contractors accountable for delivery performance, and giving leadership a clear, converged picture of delivery risk across the portfolio. Your job is to make sure equipment production and delivery are never the reason a site misses its ready-for-service date. This is a senior individual-contributor role on the Compute DC Infrastructure team, working daily with Construction, Electrical and Mechanical Engineering, Strategic Sourcing, Commissioning, and our general contractors and OEMs. It is not a category-management or negotiation role — Sourcing owns supplier strategy and commercial terms — and it is not a people-management role. The emphasis is execution: schedules, escalations, logistics, and site readiness. What You'll Do Delivery planning and schedule integration Own the end-to-end OFE delivery plan for each site in your portfolio: order placement, engineering submittal/approval milestones, production slots, FAT dates, ship dates, and required-on-site (ROS) dates, integrated with the GC's construction schedule. Engage during preconstruction with Construction, Engineering, and the GC to set OFE delivery expectations, sequence equipment arrivals to the build, and identify schedule risk before POs are cut. Lead OFE kickoff meetings at the site level with the GC and internal construction teams, establishing points of contact, delivery windows, receiving requirements, and escalation paths. Maintain the single source of truth for OFE status across the portfolio — a live tracker of every line item, its milestone dates, and its risk rating. Supplier execution and escalation Run weekly delivery cadences with OEMs and integrators on open orders; verify production progress against committed slots rather than accepting reported dates at face value. Act as the primary escalation point for factory slips, component shortages, FAT failures, and shipping delays; drive recovery plans (expedites, partial ships, resequencing, alternate sources) with Sourcing and Engineering. Partner with Sourcing on corporate-level supplier escalations, bringing site-level schedule intelligence to commercial conversations. Hold GC OFCI teams accountable for receiving, storage, and installation-readiness performance; manage the change/claim process when delivery issues affect the GC's schedule. Logistics and site readiness Plan and coordinate transportation for oversize/overweight and high-value equipment — carrier selection, route surveys, permits, crane and rigging coordination — with our logistics partners and the GC. Manage laydown, staging, and interim storage decisions when site readiness and equipment arrival diverge; coordinate with Quality and Commissioning on receiving inspection and storage/preservation requirements. Ensure equipment arrives complete — accessories, spares, documentation, and vendor startup support scheduled — so installation and commissioning are not delayed by missing pieces. Risk management and reporting Identify, triage, and report delivery risks across the portfolio; propose solutions and drive decisions to protect capacity milestones. Establish and lead recurring Capacity Delivery Reviews giving leadership converged visibility into OFE delivery status and risk by site and by equipment category. Track delivery KPIs — on-time-to-ROS, schedule drift by supplier and category, escalation cycle time, expedite spend — and use them to surface systemic issues. Feed lessons learned back into Sourcing (lead-time assumptions, contract delivery terms, buffer strategy) and Construction (ROS sequencing) to improve the next program. Who You Are 8–12+ years in supply chain delivery, equipment expediting, construction management, or infrastructure program management on large-scale, schedule-driven construction programs. Hands-on experience delivering power and/or cooling equipment for mission-critical facilities — transformers, switchgear, generators, UPS, busway, chillers, CDUs, air handlers — and familiarity with how those OEMs actually build and ship. You've managed cross-functional escalations across construction teams, suppliers, and internal partners, and you know when to expedite, when to resequence, and when to escalate commercially. Comfortable reading and influencing construction schedules (P6 or MS Project) and tying equipment milestones to them. Strong written and verbal communication — you can turn a messy delivery problem into a one-page recommendation for leadership. Data-fluent: you build and maintain trackers and dashboards, and you'd rather look at the numbers than trust a status email. Thrive with high autonomy in a fast-moving, ambiguous environment; you own outcomes, not just updates. Bachelor's degree in Supply Chain, Engineering, Construction Management, or a related field, or equivalent experience. Nice to Have Experience with hyperscale or AI data center construction and OFCI (owner-furnished, contractor-installed) delivery models. Experience supporting multiple concurrent projects (5–10+) across a regional portfolio. Working knowledge of FAT/SAT and commissioning workflows and how equipment documentation gates them. Heavy-haul / project logistics experience, including international freight, customs, and Incoterms. Technical understanding of data center electrical distribution and cooling system design. Familiarity with ERP/procurement systems and analytics tools (SQL, Power BI/Tableau, Smartsheet/Procore). PMP, CSCP, or similar certification. Logistics Location: [San Francisco / hybrid, or remote US near the regional portfolio?] Travel: [up to 40%] to construction sites in the regional portfolio and to supplier factories as needed. 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: $320,000 — $405,000 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. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. 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.

Location: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We are seeking a Senior Systems Engineer – Software & Autonomy to support the definition, architecture, integration, and verification of the software systems that enable our humanoid robotic platform. The role will work across perception, localisation, navigation, artificial intelligence, motion planning, controls, ROS 2 platform software, simulation, deployment, and diagnostics. You will collaborate with software leads and subject matter experts to translate product and operational needs into coherent capabilities, requirements, architectures, interfaces, integration plans, and verification criteria. This is a systems engineering position focused on the robot’s software and autonomy stack. It is not primarily a firmware development or electrical engineering role. WHAT YOU'LL DO - Obtain input from system leaders, product teams, and technical subject matter experts to translate stakeholder needs into clear and verifiable system and software requirements. - Define the software capabilities required to support humanoid robot behaviours, operational use cases, and product objectives. - Decompose system-level capabilities across perception, navigation, AI, planning, controls, core platform, and supporting software services. - Develop and maintain the functional and logical architecture of the robot’s software and autonomy stack. - Define system boundaries, responsibilities, dependencies, and interfaces between software components and technical teams. - Establish interface requirements covering data ownership, message definitions, coordinate frames, units, timing, latency, synchronization, quality indicators, fault handling, and degraded operation. - Support architectural decisions involving, middleware, compute allocation, networking, simulation, software deployment, and distributed execution. - Coordinate integration across perception, navigation, AI, controls, platform software, firmware, electronics, sensors, actuators, and mechanical systems. - Identify cross-team assumptions, dependencies, architectural conflicts, and missing functionality before they become late-stage integration issues. - Define integration stages, entry and exit criteria, required test environments, and readiness expectations. - Lead or support the investigation of complex system-level issues involving multiple software components or interactions between software and hardware. - Define nominal, degraded, recovery, fallback, and safe-state behaviours for software-intensive functions. - Develop system-level verification and validation strategies for autonomous robotic capabilities. - Establish measurable performance and acceptance criteria for perception, localization, navigation, planning, controls, AI, and integrated robot behaviours. - Support scenario-based testing using simulation, software-in-the-loop, hardware-in-the-loop, laboratory testing, and physical robot testing. - Maintain traceability between use cases, requirements, architecture, implementation, tests, and verification evidence. - Work with safety engineers to ensure software behaviours support system safety requirements and hazard mitigations. - Facilitate requirement, architecture, interface, integration, and system-readiness reviews. - Communicate technical risks, capability limitations, integration status, and architectural trade-offs to engineering and program leadership. - Coach engineering teams in practical systems engineering methods appropriate for an iterative robotics development environment. WHAT WE'RE LOOKING FOR - Bachelor’s or Master’s degree in Systems Engineering, Software Engineering, Computer Science, Robotics, Mechatronics, Controls Engineering, or a related field. - Five or more years of experience in systems engineering, robotics software, software architecture, autonomous systems, or a related technical domain. - Experience working with complex software-intensive or cyber-physical systems composed of multiple interacting subsystems. - Strong knowledge of requirements engineering, architecture definition, interface management, integration, verification, validation, and traceability. - Technical experience in several of the following areas: - ROS or ROS 2 - Robotics software - Perception and sensor fusion - Localization, mapping, and navigation - Motion or behaviour planning - Manipulation, locomotion, or whole-body controls - Artificial intelligence or machine learning - Simulation and virtual testing - Distributed or real-time software systems - Ability to understand and evaluate software behaviour without being the primary implementation owner for every component. - Experience defining measurable acceptance criteria for complex system behaviours. - Ability to investigate issues spanning algorithms, software, computing, networking, firmware, sensors, actuators, and physical robot behaviour. - Strong analytical, problem-solving, leadership, and technical communication skills. Experience with humanoid robots, mobile robots, autonomous vehicles, industrial robotics, or similar systems. - Familiarity with ROS 2 topics, services, actions, quality-of-service policies, lifecycle management, TF, rosbag, and distributed execution. - Familiarity with C++, Python, Linux, Git, CI/CD, containers, and modern software development workflows. - Experience with simulation tools such as Isaac Sim, Gazebo, MuJoCo, MATLAB/Simulink, or equivalent platforms. - Experience with SysML, model-based systems engineering, or software architecture modelling. - Familiarity with functional safety, SOTIF, machinery safety, cybersecurity, or safety assurance for autonomous systems. - Understanding of machine-learning performance, uncertainty, dataset coverage, and scenario-based validation. WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Location: San Francisco, United States About the Opportunity We are partnering with an innovative early-stage robotics company developing intelligent automation solutions for industrial manufacturing. The team is building advanced robotic systems that combine perception, motion planning, and real-time control to solve complex automation challenges in production environments. This is an opportunity to join a small, highly technical engineering team where you'll have significant ownership, work directly with robotics hardware, and help build core technology from the ground up. What You'll Do Design, develop, and maintain robust software for industrial robotic systems. Build and optimize motion planning, trajectory generation, and real-time control algorithms. Develop vision-based robotic applications by integrating cameras and other sensors. Improve system performance, reliability, and scalability across embedded and cloud-based environments. Write clean, modular, well-tested code following software engineering best practices. Perform simulation, testing, and real-world validation of robotic systems. Collaborate closely with software, hardware, and controls engineers to deliver integrated robotic solutions. Contribute to system architecture and technical design decisions. What We're Looking For Required Qualifications Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or a related technical field. Strong software development experience in Python. Solid understanding of robotics fundamentals, including: Kinematics Dynamics Control theory State estimation Experience with Git, software testing, and debugging. Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment. Must be authorized to work in the United States without future sponsorship due to export control requirements. Preferred Qualifications Master's degree in Robotics, Computer Science, or a related field. Experience with ROS or other robotics middleware. Experience with motion planning, trajectory optimization, and real-time robotic control. Experience working with industrial robot arms or robotic manipulation systems. Familiarity with computer vision and 3D perception. Experience optimizing software for embedded or edge computing platforms. Knowledge of distributed systems or cloud-based robotics infrastructure. Ideal Background We're especially interested in engineers who have experience developing software for robotic manipulation systems in industrial, manufacturing, or automation environments. Candidates who enjoy building new systems from the ground up, working across hardware and software, and taking ownership of challenging technical problems will thrive in this role. What You'll Find Opportunity to work on cutting-edge robotics technology. High-impact engineering role with meaningful ownership. Collaborative, fast-moving technical team. Competitive compensation and equity package. Relocation assistance may be available for qualified candidates.

Location: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We are looking for a Robotics Test Engineer to support software release validation, policy evaluations, and end-to-end metrics collection on our humanoid robots. You will work alongside our Test Team, owning day-to-day execution and growing into deeper HIL and automation responsibilities. This is not a standard web-QA role. You will be running tests on real robots, comparing simulation against reality, and helping us build the data pipeline that tells us whether each new software version is ready to ship. WHAT YOU'LL DO SOFTWARE RELEASE TESTING - Release Validation: Execute the end-to-end test pipeline for each new software release, ensuring quality gates are met before the build is deployed to the fleet. - Regression Coverage: Run automated and manual regression suites against new builds; triage failures and route them to the right owner. - CI/CD Participation: Contribute new tests to our CI/CD pipeline (GitLab CI, GitHub Actions) so that regressions are caught immediately after code merges. 2. POLICY EVALUATIONS - Eval Support: Help design and run policy evaluations for our learned behaviors — defining success criteria, executing trials, and collecting results in a reproducible way. - Simulation: Run policy evaluations in simulation environments (Gazebo, NVIDIA Isaac Sim) in parallel with physical robot tests. - Sim-to-Real: Track differences between simulation and physical robot results and feed findings back to the policy team. 3. E2E METRICS COLLECTION - Metrics Pipeline: Support the collection of end-to-end performance and reliability metrics across releases, building consistent reporting the org can trust. - Dashboards: Help maintain dashboards that highlight pass/fail rates, latency, and performance trends release-over-release. - Data Hygiene: Keep test data clean and well-labeled so that long-term trends remain meaningful as the platform evolves. WHAT WE'RE LOOKING FOR - Experience: 3+ years in software test engineering or test automation, ideally with some exposure to robotics, embedded systems, or another physical-systems domain. - Coding: Strong proficiency in Python for scripting and test automation. Comfortable reading C++. - Robotics Middleware: Working knowledge of ROS2 — you understand topics, services, and how to interact with a running robot. - OS: Comfortable in Linux (Ubuntu) — terminal, shell scripting, basic system administration. - Mindset: Methodical and curious. You enjoy finding the one weird edge case that breaks the build. Nice-to-Have: - Experience with robotics simulators (Gazebo, NVIDIA Isaac Sim, Unity). - Exposure to Hardware-in-the-Loop (HIL) test benches. - Basic electrical debugging skills (multimeter, oscilloscope). - Awareness of safety-critical standards (IEC 61508, ISO 26262). TECH STACK - Languages: Python (primary), C++ (reading), Bash - Robotics: ROS / ROS2 - CI/CD: GitLab / GitHub Actions - Simulation: NVIDIA Isaac Sim - Hardware Interfaces: CAN, EtherCAT, Ethernet WHAT WE OFFER - Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays. - Fully funded private healthcare for UK employees, with broad provider access, virtual and in‑person care, and strong mental health and serious illness support. - Equity included–we believe builders should share in what they build. - Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in‑office. - Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics. - Freedom to influence the product and own key initiatives.

Location: China Workplace: OnSite ABOUT HUMAN ARCHIVE Human Archive is a research lab backed by Y Combinator focused on modeling human embodied intelligence. Humans are the most sophisticated biological systems we have ever observed, yet we still do not fully understand ourselves. Research into human physical intelligence — including the human hand, proprioception, and vision — remains largely unsolved. Our mission is to recover human embodied intelligence as a learned model. To achieve this, we build custom hardware products, deploy them globally at scale, and publish research. Today, our data is used for robotics and world modeling, but the broader opportunity is advancing scientific research into intelligence itself. Founded by Stanford and UC Berkeley researchers, we are lean, deeply technical, and operate at extreme speed, taking on unglamorous and conventionally impossible problems that directly unlock step-function gains in model capability. The deployment of capable humanoids at scale will permanently redefine human labor. Undesirable physical work will disappear, and human effort will shift toward a new era of abundant creativity. We are building the infrastructure to accelerate that transition by assembling the Human Archive mafia. You will own meaningful systems from day one and see your work directly impact model capabilities. This is a once-in-a-generation inflection point. If you want to help reshape physical labor and work on problems that matter at civilizational scale, join us. What you'll work on We're hiring a firmware engineer to own the embedded software stack on our wearable capture hardware. Close-to-the-metal work at the intersection of high-bandwidth sensor data, precise timing, and constrained-power embedded compute. You read schematics, debug buses, and know when the bug is in firmware versus when it's in hardware. System architecture - Firmware architecture on embedded Linux on ARM - System state machines: boot, capture, idle, fault recovery - Power management states and low-power transitions Sensor integration and timing - Drivers for cameras, IMUs, microphones, environmental sensors - Sub-millisecond cross-sensor synchronization - Hardware-level timestamping infrastructure - Real-time sensor data alignment - Lightweight on-device fusion for orientation and worn-state estimation (Kalman variants) Data pipeline - Multi-stream concurrent capture - Hardware video encoder pipelines - High-throughput storage writes - Industry-standard delivery format packing Connectivity and fleet operations - Device-to-backend telemetry (battery, storage, session state, error events) - Secure OTA firmware updates with signed images and rollback protection - Remote configuration and fleet management commands - Communication protocols for device-cloud messaging (MQTT-over-TLS, HTTPS, WebSockets) Hardware / software bring-up - Firmware-side board bring-up alongside electrical engineers - Validate hardware interfaces (I²C, SPI, USB, MIPI) - Diagnose timing, power sequencing, and communication faults Required technical experience - Strong C/C++ for embedded systems on ARM - Python for testing, tooling, and automation - Camera driver experience (V4L2 or equivalent) - Deep familiarity with embedded interfaces: MIPI CSI-2, I²C, SPI, USB, interrupts - Comfortable reading schematics and datasheets Systems and concurrency - Interrupts, race conditions, memory constraints, real-time scheduling - RTOS concepts and multi-threaded embedded environments Strong plus - Qualcomm, NXP, or Ambarella BSP experience - SerDes driver integration - Hardware H.264 / H.265 encoder pipelines - Precise timing and synchronization (PTP, IEEE 1588) - High-bandwidth data acquisition - Sensor fusion and Kalman filter implementation - OTA infrastructure for deployed fleets - IoT telemetry stacks (MQTT, AWS IoT, Azure IoT Hub, or similar) - ROS, MCAP, or Foxglove About this role Deep systems work. Long hours in the lab during board bring-up. Drivers nobody has written for the silicon you're working with. Firmware that runs unattended on real users for full shifts — and gets updated remotely without ever recalling a device.

Location: Singapore, Singapore OKX will be prioritising applicants who have a current right to work in Singapore, and do not require OKX's sponsorship of a visa. Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Opportunity We are looking for a Senior Staff Engineer/Engineering Director who will be responsible for the design, deployment, optimisation, and full lifecycle management of enterprise-level cloud database platforms. Lead the implementation of multi-cloud architectures for Alibaba Cloud and AWS databases, ensuring high availability, high performance, and cost optimization. What You'll Be Doing Database Architecture Design & Optimization Design, deploy, and optimize cloud databases on Alibaba Cloud (RDS, PolarDB, Redis, MongoDB) and AWS (RDS, Aurora, ElastiCache, DynamoDB). Select appropriate database types (relational/NoSQL/NewSQL) and service models (managed services vs. self-built clusters) based on business requirements. Operations & Monitoring Implement high availability (HA) and disaster recovery (DR) solutions, such as Alibaba Cloud cross-zone deployments, AWS Multi-AZ, and cross-region replication. Monitor database performance and health using cloud-native tools (Alibaba Cloud CloudMonitor, AWS CloudWatch) and third-party tools (Prometheus, Grafana). Performance Tuning & Incident Resolution Analyze slow queries, lock conflicts, and resource bottlenecks (CPU/IO/memory), optimizing SQL statements and index designs. Rapidly resolve production database incidents (e.g., replication lag, connection pool exhaustion, storage scaling). Security & Compliance Manage database access controls via Alibaba Cloud RAM policies and AWS IAM roles to ensure data security. Perform regular database upgrades and audit log analysis to comply with GDPR, Multi-Tier Cloud Security Certification (MLPS), and other regulations. Automation & Cost Management Automate database deployment and operations using Terraform, Ansible, or cloud-native tools (Alibaba Cloud ROS, AWS CloudFormation). Optimize cloud costs via auto-scaling, reserved instances, and storage tiering (e.g., AWS S3 Glacier). Cross-Team Collaboration Support development teams in database design reviews, SQL code standardization, and DevOps processes (e.g., database change management in CI/CD). Team Management Manage a team of DBAs to ensure timely completion of projects and efficient resolution of incidents. What We Look For In You Technical Skills Expertise in database services of at least one major public cloud (Alibaba Cloud or AWS), with familiarity in the other. In-depth understanding of core principles of mainstream databases (MySQL, PostgreSQL, Redis) and advanced SQL optimization/troubleshooting skills. Experience with database migration tools (AWS DMS, Alibaba Cloud DTS) and cross-cloud synchronization solutions. Experience Requirements 5+ years of DBA experience, including at least 2 years managing public cloud databases. Hands-on experience with large-scale (TB-level) databases, sharding, and read/write splitting. Experience leading cloud database migrations, DR drills, or hybrid cloud projects is preferred. Soft Skills Strong documentation skills for creating SOPs and contingency plans. Excellent communication skills to coordinate development, operations, and business teams. Certifications & Education Alibaba Cloud ACP/ACE (Database) or AWS Certified Database – Specialty certifications preferred. Bachelor’s degree or higher in Computer Science, Software Engineering, or related fields. Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .