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Location: Santa Clara, CA Workplace: onsite About Welo Data Welo Data, a Welo Global brand, is the multilingual data and evaluation partner for foundation labs and enterprises deploying GenAI systems globally. They deliver the human judgment, data infrastructure, and evaluation systems that ensure AI models perform reliably across languages, cultures, and real-world contexts, at every stage from training through deployment.  Its global network of 500,000+ vetted experts spans 300+ languages and locales, enabling high-quality multilingual data creation and structured model evaluation across the full spectrum of modern AI applications — from large language models and voice and speech systems to agentic workflows and robotics and embodied AI. This breadth of linguistic, cultural, and domain expertise enables Welo Data to address critical AI development challenges, including safety, bias, inclusivity, and cross-lingual reliability. A unified global operating model, led by specialized program and quality experts and grounded in assessment-driven talent selection, localized rubrics, and continuous calibration, ensures consistent performance across languages, domains, and modalities. Underpinning all of this is NIMO™ (Network Identity Management and Operations), Welo Data's proprietary identity and fraud-prevention framework. Built to maintain data integrity and workforce trust across a global contributor base, NIMO combines advanced verification, continuous monitoring, and structured QA to ensure every dataset is accurate, traceable, and culturally grounded. welodata.ai    Role Overview You own a shift. Not a zone of it, not a function within it — the whole thing. Roughly 140 operators, 13 Cell Leads, and 3 Operations Supervisors collecting robot demonstration data, and you are the single person accountable for what that shift produces, how good it is, and whether everyone goes home safe. The shift you own runs whether or not the Production Manager is in the building. That's the job: your shift should be indistinguishable in output and quality from the one before it and the one after it. What You Will Do Own your shift's production plan end to end — accepted episodes, first-pass acceptance, utilization, and labor efficiency against target. Manage 2–3 Operations Supervisors; own their performance, their development, and the quality of the Cell Lead bench underneath them. Run shift start-up, mid-shift review, and a documented handoff — you receive the shift before yours and hand off cleanly to the shift after. Make the real-time calls: redeploying staff when a cell goes down, resequencing work when a task type stalls, flexing coverage when attendance comes in short. Own safety on your shift — daily walks, protocol enforcement, incident response, and the expectation that your supervisors use: their stop-work authority. Partner with Data Quality on your shift's acceptance rate; drive root cause into retraining and process rather than into a rework queue. Escalate equipment and rig issues to Lab Engineering and keep staffed-but-idle hours visible. Handle performance management and employee relations escalations from your supervisors, partnering with HR. Hold California meal, rest, and overtime compliance across every non-exempt employee on your shift. Report your shift's performance and variance daily, with the explanation and the fix, not just the number. What Good Looks Like Your shift hits plan without overtime surprises or last-minute heroics. Handoffs are clean enough that the next shift starts producing immediately. Your supervisors make decisions without calling you, and your Cell Leads are being prepared for supervision. Quality on your shift doesn't vary from the other shifts — consistency is the whole point of this layer. Problems reach the Production Manager as "here's what happened and here's what I did," not as an open question. Basic Qualifications 5+ years in production, manufacturing, warehouse, or lab operations, including 2+ years managing supervisors or team leads. Experience with full accountability for a shift or a production area of 75+ hourly employees. Track record owning daily output and quality targets, and explaining variance credibly. Experience with performance management, attendance, and employee relations for a non-exempt workforce. Working knowledge of California wage and hourly requirements for non-exempt employees. Available to own an assigned shift (day, swing, or night) onsite in Santa Clara. Preferred Qualifications Robotics, hardware, AI data collection, advanced manufacturing, or technical lab background. Experience in a quality-gated operation where output is inspected before it counts. Promoted from a supervisor role, or has promoted supervisors from their own team. Comfort pulling and interpreting your own shift data from dashboards or spreadsheets. Continuous improvement background — Lean Six Sigma, or equivalent practical experience. Bilingual (English/Spanish). Work Environment and Physical Requirements Onsite robotics lab and warehouse environment; the majority of your shift is spent on the floor. Assigned shift, with occasional cross-shift coverage during ramps, launches, and handoff issues. Must be able to stand and walk the floor for extended periods. Must be able to occasionally lift and/or move up to 25 lbs. Why This Role Matters Consistency across shifts is what turns a lab into an operation. This role is the reason the third shift produces like the first one, and the reason problems get solved on the floor instead of escalating. Benefits Included in the Offer: - Friendly Working Environment - IT Equipment - Social Activities - Global Mobility Policy - Employee Referral Program - Employee Assistant Program - Medical, Dental, and Vision Insurance - HSA & FSA - 401(k) retirement - Short & Long Term Disability Insurance - Accident, Critical Illness, Hospital Indemnity Insurance  - Telemedicine Benefit - Annual Leave - Paid Public Holidays - Maternity/Paternity Leave   Hourly Pay: $71-$81/hour.   Job Reference: #LI-JC1

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: Singapore ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. ABOUT THE JOB Mistral AI is seeking Applied Scientists and Research Engineers focused on robotics. You will design, train, and deploy SOTA robotics models (VLM, VLA models for navigation and manipulation) and apply them to diverse use cases. You'll work cross-functionally with internal and external science, engineering, and product teams to deliver high-impact AI solutions. WHAT YOU WILL DO - Run pre-training, post-training and deploy state of the art models on large clusters. - Generate and curate datasets (image-text, video-text), and build evaluators/benchmarks for perception, navigation and manipulation tasks. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases. - Manage research projects and communications with client research teams. ABOUT YOU - Fluent in English with excellent communication skills. - Expert with PyTorch or JAX. - Experience with Vision Language Models (VLM), Vision-Language-Action (VLA) models, perception, navigation and manipulation, simulation tools (e.g. Isaac SIM). - Clean, readable, high-performance Python code. - Doesn't need roadmaps. Ships. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. NICE TO HAVE - PhD / Master in a relevant field (Robotics, Machine Learning). - Research experience in robotics navigation, perception, manipulation. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Singapore ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. ABOUT THE JOB Mistral AI is seeking an Applied AI Engineer focused on robotics deployment. You will take state-of-the-art AI models and make them work on real robots, in real environments, for real customers. This is a hands-on role at the intersection of machine learning and physical systems: you will own the path from model to deployed autonomy, working alongside robotics engineers, ML researchers, and systems engineers to deliver end-to-end autonomous solutions across diverse use cases. WHAT YOU WILL DO - Integrate AI models with robotic hardware, sensors, and embedded systems, bringing modern perception and language-driven capabilities onto physical platforms. - Improve the robustness, reliability, and safety of robotic systems operating in real-world, unstructured environments. - Test and validate algorithms in simulation and in real-world deployments, moving fluidly between the two. - Analyze field data to improve model performance and system reliability, closing the loop between what happens on the robot and what happens in training. - Bring up, tune, and debug the autonomy stack — localization, mapping, navigation, and perception — on real hardware, from sensor calibration to real-time performance. - Develop and tune robot navigation behaviors — path planning, obstacle avoidance — so systems hold up in dynamic, cluttered, and partially observable environments. - Diagnose failures end-to-end: mapping drift, localization dropouts, perception edge cases, timing issues — and fix them. - Collaborate with robotics engineers, ML researchers, and systems engineers to deliver complete autonomous solutions for customer use cases, from prototype through production deployment. - Build and maintain the tooling needed for deployment, monitoring, and continuous improvement of deployed systems. ABOUT YOU - Bachelor's, Master's, or PhD in Mechatronics, Robotics, or a relevant discipline (e.g. Computer Science, Electrical or Mechanical Engineering). - Fluent in English with excellent communication skills. - Strong software engineering in Python and/or C++: clean, readable, high-performance code; comfortable working in and improving production codebases. - Knowledge of robotics frameworks such as ROS/ROS2. - Experience with robot perception and state estimation: SLAM, localization and mapping, path planning, sensor fusion, or computer vision. - Solid mathematical fundamentals — geometry, probability, and estimation — and the judgment to know when a hand-crafted algorithm beats a learned one. - Familiarity with simulation tools and robotics development environments (e.g. Isaac Sim, Gazebo, or similar). - Strong problem-solving skills and ability to work in interdisciplinary teams. - Comfortable with the messiness of the real world: hardware quirks, edge cases, and field surprises don't scare you. - Low-ego, collaborative, and eager to learn. - Doesn't need roadmaps. Ships. NICE TO HAVE - Experience deploying ML models on embedded or edge hardware (GPU/NPU inference, quantization, real-time constraints). - Hands-on experience with sensor modalities such as LiDAR, depth cameras, or IMUs, including calibration and time-synchronization. - Exposure to VLM/VLA models or other foundation-model approaches for robot perception and control. - Experience with navigation in GPS-denied or otherwise challenging environments, or with visual-inertial odometry. - Working knowledge of established autonomy tooling — e.g. Nav2, SLAM Toolbox, Cartographer, RTAB-Map, or AMCL — and knowing when to build versus reuse. - Experience with behavior trees, dynamic costmaps, or fleet-level navigation. - Contributions to open-source robotics or ML projects. - Experience with safety-critical or regulated deployment environments. - Track record of success through personal projects, professional projects, or academia. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: 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: 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 Staff Robotics Control Engineer to join our Control Team in London and lead the evolution of whole-body control for our Wheeled Alpha platform - a humanoid whose whole body spans a wheeled base, torso and two arms, controlled as one coordinated system. We need genuine depth in classical whole-body control. You should know hierarchical and weighted QP formulations from the inside - not as a library you have called, but as something you have derived, implemented, tuned, profiled and debugged on real hardware under demo pressure. You should have opinions about strict hierarchies versus soft-weighted stacks, regularisation and nullspace behaviour, what to do when a task set becomes infeasible, and how to keep a redundant system clear of singularities without it feeling sluggish. Alongside that depth, you will set technical direction and mentor a strong team of control engineers. WHAT YOU'LL DO Whole-Body Control Architecture & Algorithms: - Lead the evolution of the Wheeled Alpha whole-body controller: task formulation, prioritisation, weighting, constraint handling and solver selection. - Coordinate wheeled base, torso and dual-arm motion within a single whole-body formulation, with base motion that tracks commanded targets accurately and stays well-behaved under aggressive commands and long-duration operation. - Own the constraint layer - self-collision avoidance, joint and velocity limit guarding, and singularity handling - plus feasibility handling and recovery when the solver fails. - Drive the evolution toward predictive formulations: evaluate and develop MPC-based whole-body control where anticipating dynamics and constraints outperforms instantaneous QP resolution. Dynamics, Compliance & Payload: - Own the dynamic models the controller runs on - inertial, gravity and friction modelling, system identification, and online payload estimation - so the robot knows what it is carrying and controls accordingly. - Advance compliance and force behaviour - impedance, admittance and force control that stays compliant at contact - and extend payload capability without sacrificing either. - Own stability-aware behaviour under changing payload and dynamic motion Safety Integration: - Make whole-body control a first-class citizen of the safety architecture: the controller must accept and honour requests from dedicated safety compute - velocity capping, controlled deceleration, constrained operating envelopes - provably and without degrading motion quality. - Co-own the controls-to-safety interface with the safety team, and design control behaviour so that safety interventions are graceful rather than abrupt. Technical Leadership: - Define the performance metrics for whole-body control and insist on deterministic, reproducible evaluation of every change, in simulation and on hardware. - Mentor control engineers on optimisation-based control, numerical robustness and hardware debugging; act as reviewer of record for the most consequential changes. - Work with hardware teams so control constraints and mechanical design decisions stay coherent. WHAT WE'RE LOOKING FOR - Deep, demonstrable expertise in optimisation-based whole-body control: hierarchical and weighted QP formulations, task prioritisation, constraint handling, and the numerical realities of solving them inside a real-time loop. - Strong command of the classical WBC toolkit - operational space and task-space control, inverse dynamics and IK formulations, redundancy resolution, nullspace projection, impedance and admittance control, contact and force control - and working knowledge of MPC formulations for whole-body or mobile-manipulation control. - Deployed whole-body controllers on real high-DoF hardware (humanoids, mobile manipulators, dual-arm or legged platforms), including coordinating base and manipulator motion. - Practical fluency with QP/NLP solvers and their failure modes: conditioning, infeasibility, warm starting, solve-time budgets, and what to do at the limit. - Strong dynamic modelling foundations: rigid body kinematics/dynamics (Jacobians, dynamics formulations, URDF-based modelling), inertial and friction system identification, and payload/external-load estimation. - Expert modern C++ for real-time control with Python for analysis and prototyping. - Track record of taking control algorithms to production reliability rather than to a paper or a one-off demo, plus demonstrated technical leadership and mentoring. 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: US, Boston, MA 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 Controls Engineer to join our Control Team in Boston. You will own how we know our controls stack works: the testing and validation infrastructure that turns "it looked fine on the robot" into measured, reproducible evaluation, the observability and failure analysis that makes runtime behaviour visible and failures shareable, and the documentation and runbooks that let the team self-serve without institutional knowledge. You will also strongly contribute to first-time bring-up of new hardware for Boston components and validate changes end-to-end on real robots before the wider team depends on them. The ideal candidate has strong control fundamentals, solid software engineering discipline across the stack - from control code to test harnesses to diagnostic tooling - and the debugging instincts that only come from real hardware. You will work across the whole control stack and be the person the team relies on to tell them the truth about their code. WHAT YOU'LL DO Testing & Validation Infrastructure: - Build and own hardware-in-the-loop (HIL) and integration test workflows that quantify controller and motion repeatability and accuracy - turning "it looked fine on the robot" into measured, reproducible evaluation. - Define and implement repeatability and accuracy metrics for controller and motion changes, and the harnesses that make those measurements consistent across runs and across robots. - Expand unit and integration test coverage across the controls components the team actually runs - actuator drivers, hardware interfaces, whole-body control, and the teleoperation pipeline. - Develop automated regression checks that surface controls regressions - in accuracy, repeatability, or behaviour - in simulation and on hardware before they reach the wider team. - Work with controls engineers to define testability requirements for new components and algorithms, so things are built to be evaluated and validated. - Package controllers into cleanly separable, reusable, and easily testable interfaces - so individual controllers can be developed, swapped, and validated in isolation. New Hardware Bring-Up & Integration: - Strongly contribute to first-time bring-up of new hardware for Boston components, and to their integration into the controls stack. - Validate hardware and software changes end-to-end on real robots before broader team use - structured, documented, and repeatable. Debugging, Observability & Failure Analysis: - Instrument the controls stack to improve visibility into runtime behaviour - logging, tracing, and diagnostic tooling. - Reproduce hardware and software failures in structured, developer-shareable formats; feed structured root-cause context back to algorithm and hardware owners. - Identify and resolve cross-stack failure modes that span controls, firmware, and hardware. Documentation & Knowledge Transfer: - Write and maintain engineering documentation for the controls stack: HIL and test coverage, and bring-up/integration guides for new hardware. - Own runbooks that let controls engineers self-serve validation, integration, and recovery without relying on institutional knowledge. WHAT WE'RE LOOKING FOR - Substantial hands-on robotics experience on real hardware. - Strong control theory foundation (joint-space control, PID and feedforward, impedance/admittance, observers, state estimation, filtering, stability) — enough to define meaningful repeatability and accuracy metrics for a control stack and interpret what they say. - Shipped software across the stack: modern C++ inside a real-time control codebase, plus Python for test harnesses, analysis and tooling. - Built test automation, HIL or integration-test infrastructure for complex physical systems — and got other engineers to actually use it. - Solid measurement and data analysis judgement: sampling, timing and synchronisation, noise, statistical significance, and knowing when a difference between two runs is real. - Strong debugging across software/firmware/hardware boundaries, with the discipline to reproduce failures in a form other engineers can act on. Nice to have: - Physics simulation environments (MuJoCo, Isaac Sim/Isaac Lab) and sim-to-real validation. - Observability tooling: logging and tracing frameworks, metrics collection, time-series databases, dashboarding (e.g. Grafana). - First-time hardware bring-up experience: new actuators, sensors or compute targets integrated into a control stack. - A track record of engineering documentation and runbooks that outlived their author. - Release management or quality gates for safety-relevant software. WHAT WE OFFER - Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources. - Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays. - 401(k) retirement plan with 4% employer match. - Competitive equity: stock options with meaningful upside as we scale. - Free daily catered lunch, snacks, and drinks 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: Philippines; India; Mexico City, Mexico; Mexico; Cairo, Egypt; Brazil; Malaysia; Indonesia Workplace: remote About the Role  We are looking for a detail-oriented QC Reviewer to ensure the quality and consistency of robot manipulation video annotations produced by our annotation team. You'll review labeled video segments against a detailed style guide and reference examples, catch errors or inconsistencies, and provide clear, constructive feedback to annotators. This role is critical to maintaining the accuracy and reliability of training data used for robotics AI models.  What You'll Do      - Review completed annotations of robot manipulation videos across three levels of labeling detail (atomic motion, skill/subtask, task/goal).      - Cross-check annotator descriptions against all three camera views (overhead and both wrist-mounted cameras) to verify accuracy of described actions, object identification, and contact/grasp details.      - Verify full coverage of each video — confirm there are no gaps in labeling, including idle or pause moments.      - Check that descriptions accurately reflect what actually happened in the video, including failures, drops, or slipped grips — flagging any instances where outcomes were inaccurately described or "smoothed over."      - Evaluate annotations for adherence to the style guide: correct vocabulary usage, spatial/directional accuracy, consistent terminology for objects and actions, and appropriate language variation (avoiding repetitive phrasing).      - Identify recurring errors or patterns of confusion among annotators and report them to the team lead for calibration purposes.      - Provide specific, actionable feedback on rejected or revised annotations, referencing the style guide and reference examples.      - Participate in periodic calibration sessions with the team and client to align QC standards with evolving guidelines or edge-case resolutions.      - Maintain a QC log or tracking sheet documenting review outcomes, common error types, and annotator performance trends (as required by the project).    What We're Looking For  Required:      - Excellent written English and strong reading comprehension — you'll be evaluating precise, nuanced language choices, not just checking for typos.      - Exceptional attention to detail — able to catch subtle mismatches between video content and written description (e.g., a mislabeled grasp type, an incorrect object part, a missed failure event).      - Strong grasp of spatial/mechanical description (left/right, above/below, object parts like handles, lids, edges) to verify annotator accuracy.      - Ability to apply a detailed, structured style guide consistently and make sound judgment calls in ambiguous or edge-case scenarios.      - Comfort giving clear, specific, and constructive feedback to annotators (written feedback, not just pass/fail marks).      - Reliable, self-directed work habits, with the ability to work independently while meeting review turnaround expectations.  Nice to Have:      - Prior experience in a QC, editing, proofreading, or annotation review role.      - Experience with video annotation, data labeling, or transcription QA specifically.      - Familiarity with robotics terminology (grippers, end-effectors, manipulation).      - Experience with annotation tools such as Label Studio, including review/approval workflows.  #L1-CC1 Why Join Welo Data?   ✨ Limitless Flexibility   Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.    🌱 Limitless Growth   Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.    🌍 Limitless Support   Be part of a global contributor community with responsive guidance and support.    💡 Real Impact   Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.     How to Apply?  Apply now by answering a few quick questions to join our database and become part of our growing community.    About Welo Data  Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.   At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.

Location: Philippines; India; Cairo, Egypt; Mexico City, Mexico; Mexico; Brazil; Malaysia; Indonesia Workplace: remote About the Role  We are looking for detail-oriented annotators to help label robot manipulation videos for AI training purposes. You'll watch short videos of robots performing manipulation tasks (filmed from three synchronized camera angles) and produce precise, structured, natural-language descriptions of the actions taking place. This work directly supports the development of robotics AI models and requires strong written English, sharp observational skills, and the discipline to follow a detailed style guide consistently.  What You'll Do  1. Watch short robot manipulation videos, each filmed from three synchronized camera views (an overhead view and views from each of the robot's two wrist-mounted cameras).  2. Break each video into time segments and write clear, natural-language descriptions for each segment.  3. Apply labels at three levels of detail for each applicable segment:  - Atomic motion (a few seconds) — a single small movement (e.g., "close fingers around the red handle")  - Skill / subtask (several seconds to ~20 seconds) — a complete, meaningful action (e.g., "pick up the red block by its edge")  - Task / goal (up to ~1 minute) — the overall purpose of a sequence of skills (e.g., "place all blocks in the container")    4. Ensure every moment of video is covered by a label at two or more of these levels — no gaps, including idle or pause moments.  5. Accurately describe exactly what happens, including when something doesn't go as planned (a dropped object, a failed grasp, a slipped grip). Precision matters more than making the robot look successful.  6. Cross-reference all three camera angles: use the overhead view to understand the overall scene and object identity, and the close-up wrist views to confirm exact contact and grasp details.  7. Follow a detailed style guide covering vocabulary for actions, spatial relationships, object descriptions, and manner of movement, applying it consistently across many episodes.  8. Participate in periodic calibration sessions to align your labeling with the team and the client's reference examples.    What We're Looking For  Required:  1. Strong written English — you'll write dozens of short, precise descriptive sentences per video and need to vary your language rather than repeating the same phrases.  2. Sharp attention to detail — able to distinguish small differences (a successful grasp vs. a fumble, a push vs. a drag, which specific object part is being touched).  3. Comfort following a detailed, structured style guide and applying it consistently, even in ambiguous or edge-case scenarios.  4. Basic comfort with spatial/mechanical description (left/right, above/below, naming object parts like handles, lids, or edges).  5. Reliable, self-directed work habits — this is often heads-down work with periodic check-ins rather than close supervision.  Nice to Have:  1. Prior experience with video annotation, data labeling, transcription, or QA work.  2. Familiarity with robotics terminology (grippers, end-effectors, manipulation) — helpful but not necessary, as the style guide is self-contained.  3. Experience with annotation tools such as Label Studio.    #L1-CC1 Why Join Welo Data?   ✨ Limitless Flexibility   Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.    🌱 Limitless Growth   Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.    🌍 Limitless Support   Be part of a global contributor community with responsive guidance and support.    💡 Real Impact   Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.     How to Apply?  Apply now by answering a few quick questions to join our database and become part of our growing community.    About Welo Data  Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.   At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.

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: Palo Alto, United States Vice President, Robot Learning Confidential | Early-Stage Robotics Startup | San Francisco Bay Area, CA About the Opportunity We're partnering with an ambitious early-stage robotics company building the next generation of humanoid telepresence systems for industrial work. The company's mission is to make dangerous, highly skilled physical work safer and more accessible by enabling expert operators to remotely control humanoid robots with real-time visual, auditory, and haptic feedback. These systems are deployed in complex environments including energy infrastructure, industrial facilities, manufacturing, and other hazardous settings. A core part of the long-term vision is transforming teleoperation data into increasingly autonomous robotic capabilities. Rather than treating teleoperation as a temporary solution, the company views it as the foundation for building high-quality robot learning systems based on real-world interaction, force feedback, and task execution. This is an opportunity to define the robot learning strategy at a company where machine learning is central to the product roadmap. The Role We're seeking a Vice President of Robot Learning to lead the company's robot learning organization and own the roadmap from teleoperation data collection through to learned policies and increasing levels of autonomy. This is a highly technical leadership role for someone who enjoys building from first principles, working closely with hardware and software teams, and translating cutting-edge robotics research into production systems. You'll have the opportunity to shape both the technical direction and the team as the company scales. What You'll Do Own the robot learning strategy and technical roadmap. Build the data pipeline that transforms teleoperation sessions into high-quality training data. Develop learning systems for contact-rich robotic manipulation using real-world demonstrations. Design and deploy imitation learning, reinforcement learning, and policy optimization approaches for physical robots. Work closely with robotics, controls, perception, and hardware engineers to build an integrated robotic system. Lead the evolution from teleoperated workflows toward progressively autonomous capabilities. Build, mentor, and grow a world-class robot learning organization. Establish technical direction, research priorities, and engineering best practices. Drive experimentation, deployment, and continuous improvement using real-world operational data. What We're Looking For Required PhD or equivalent expertise in Robotics, Machine Learning, Computer Science, or a related field. Significant experience building robot learning systems for real-world robotic manipulation. Deep expertise in imitation learning, reinforcement learning, policy learning, or related techniques. Experience working with physical robots rather than purely simulated environments. Strong understanding of contact-rich manipulation, force feedback, and real-world robotic control. Track record of shipping robotics systems from research into production. Experience leading highly technical teams or serving as the technical leader for a major robotics initiative. Preferred Experience from leading robotics organizations or research groups such as: OpenAI Robotics Google DeepMind Robotics Physical Intelligence Toyota Research Institute Figure AI Agility Robotics Covariant Skild AI Sanctuary AI Dexterity Intrinsic Boston Dynamics Other leading manipulation or humanoid robotics companies Particularly valuable experience includes: Learning from teleoperation or human demonstrations Building commercial robot learning data pipelines Manipulation in contact-rich environments Haptic interfaces or force-controlled robotics Multi-modal learning using vision, force, and proprioception Scaling robot learning infrastructure across fleets Who You Are Builder-first with a passion for deploying robotics in the real world. Comfortable operating in an early-stage, fast-moving environment. Excited by ambiguous technical problems with significant ownership. Able to balance long-term research vision with near-term product execution. Motivated by building a team, not just contributing individually. Collaborative, hands-on, and deeply technical. Why Join Define the robot learning strategy from an early stage. Build systems that operate in challenging, real-world industrial environments. Work across hardware, controls, perception, and AI to solve end-to-end robotics problems. Help shape the future of intelligent humanoid robotics. Significant technical ownership with the opportunity to build and lead a high-impact organization. Location: San Francisco Bay Area, California (onsite) Employment Type: Full-time

Location: New York, NY Workplace: OnSite We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. ABOUT THE ROLE *Open to candidates based near our NYC office or those willing to relocate. Building general world models — systems that understand and simulate reality across tasks, modalities, and domains — requires closing the loop between learned representations and real-world action. We're looking for a Robotics Engineer to bring our video-native foundation models onto real hardware: deploying world-model-based policies on real robots and making them work in the real world. You will work across the full stack of robot learning — from data collection and task design, to policy deployment, to physical evaluation. This is a hands-on, execution-oriented role at the intersection of foundation models, learned robot policies, and hardware. You'll bring deep robotics domain expertise and help us ship world-model-based robot policies end-to-end, with applications ranging from manipulation to mobile robotics. WHAT YOU’LL DO - Own the deployment loop for learned policies (VLAs, diffusion policies, World Action Models) on real robot arms: inference serving, action decoding, controller integration, latency budgets, and safety limits - Diagnose real-world policy failures — determining whether the problem is data coverage, camera/proprioception mismatch, or execution — and partner with the research team to fix it at the right layer - Design demonstration data collection protocols (task setup, camera placement, teleop conventions) that produce data our world models can actually learn from — working with our existing teleop and lab infrastructure - Partner with research to run controlled experiments connecting world model representations, data composition, and fine-tuning recipes to physical success rates - Define and run physical evaluation protocols so results are trustworthy and comparable across policy iterations - Adapt our policy recipe to partner hardware and new embodiments WHAT YOU’LL NEED - You have personally deployed software on real robot hardware and iterated to make it work — whether learned policies, motion planning, classical control, or perception-driven manipulation. You can walk through a specific system you shipped, what broke on the physical robot that didn't break in sim or testing, and how you fixed it. - Fluency in the software-to-robot interface: action/command spaces, control frequencies, observation pipelines, calibration, and how each affects real-world behavior - Comfort working at the intersection of software and physical systems: you can reconfigure a robot workspace and trace a policy failure in the same afternoon - Bonus: direct experience deploying learned policies (VLAs, diffusion policies) on real hardware; experience with video/multimodal generative models or world models Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator https://runwayml.com/world-simulator.html - GWM-1 https://runwayml.com/research/introducing-runway-gwm-1 - Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5 - General World Models https://runwayml.com/research/introducing-general-world-models - Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section - Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section - Runway Studios https://runwayml.com/studios We're excited to be recognized as a best place to work: Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024

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: 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. ROBOTICS PRODUCTION TEAM LEAD (MECHATRONICS) Humanoid is the first AI and robotics company in the UK, creating the world’s most advanced, reliable, commercially scalable, and safe humanoid robots. Our first humanoid robot HMND 01 is a next-gen labour automation unit, providing highly efficient services across various use cases, starting with industrial applications.
 OUR MISSION At Humanoid we strive to create the world’s leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into daily life and amplify human capacity. VISION In a world where artificial intelligence opens up new horizons, our faith in its potential unveils a new outlook where, together, humans and machines build a new future filled with knowledge, inspiration, and incredible discoveries. The development of a functional humanoid robot underpins an era of abundance and well-being where poverty will disappear, and people will be able to choose what they want to do. We believe that providing a universal basic income will eventually be a true evolution of our civilization SOLUTION As the demands on our built environment rise, labour shortages loom. With the world’s workforce increasingly moving away from undesirable tasks, the manufacturing, construction, and logistics industries critical to our daily lives are left exposed. By deploying our general-purpose humanoid robots in environments deemed hazardous or monotonous, we envision a future where human well-being is safeguarded while closing the gaps in critical global labour needs. About the Role As Robotics Production Team Lead, you’ll be responsible for leading a team of technicians in complex, high-velocity humanoid robotic builds. You’ll be accountable for the quality, pace, and consistency of your own output as well as that of your team, whilst clearly and concisely communicating risks and blockers to the senior leadership team. You’ll be expected to keep your team engaged and empowered, maintaining the balance between quality and speed. You’ll use your skills and expertise to facilitate the identification and resolution of electrical and mechanical build issues, partnering and engaging with subject matter experts from across the business. Furthermore, you’ll own the culture of your team, driving workshop standards and an unwavering pride in workmanship.   WHAT YOU’LL DO Leadership - Lead a team of technicians in robotics assembly, rework, and repair - Report on delivery, risks, and blockers to the department head - Own and drive team culture to ensure efficiency, safety, and quality - Lead by example as someone who embodies the values and ethics of the team they are leading. - Demonstrate and embed a continuous improvement culture within your team - Allocate and track the progress of build work orders - Unblock challenges encountered by your team, escalating blockers where necessary - Pro-actively identify delivery risks, and work with your team and the senior leadership team to address them Hands-On Assembly & Integration - Build electro-mechanical assemblies according to CAD, drawings, and work instructions. - Perform precise mechanical assembly, harness routing, sensor installation, and connectorisation. - Support first-article builds, iterations, and rapid design changes. - Flag issues early and collaborate with engineering to implement fixes.   Support Validation, Debug & Test - Assist in functional testing of subassemblies and full robots. - Identify and resolve build or performance issues in real time. - Work closely with test and integration teams to ensure system readiness.   Be a High-Speed Collaborator - Communicate clearly with engineers, fellow technicians, and operations. - Adapt quickly to changing priorities—jump in wherever help is needed. - Contribute ideas to improve speed, reliability, and quality of builds.   WE’RE LOOKING FOR - Experienced in leading teams in electromechanical assembly or engineering product development - 3+ years of experience in electromechanical assembly or hand-assembly of complex systems. - Proven ability to work with mechanical, electrical, and embedded systems - Strong attention to detail and a deep sense of build quality and safety. - Ability to read CAD, mechanical drawings, and wiring diagrams. - Hands-on experience with common tools, fixtures, soldering, harness assembly, etc. - You move fast, stay organized, and take pride in solving problems in real time. - Comfortable working in a fluid, high-urgency environment with evolving designs and short timelines. WHAT WE OFFER - Competitive salary plus participation in our Stock Option Plan - Paid vacation with adjustments based on your location to comply with local labor laws - Travel opportunities to our Boston and Vancouver offices - Office perks: free breakfasts and lunches - Freedom to influence the product and own key initiatives - Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics - Startup culture prioritising speed, transparency, and minimal bureaucracy.

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're hiring a strong Robotics Learning Engineer to join our Manipulation team based in London. In this role, you will work on teaching our robots to manipulate the world around them. This is a role at the intersection of applied deep learning and robotics, and to be set up for success you need both experience of working with real robot hardware (e.g. identifying issues in control or teleop), and applied deep learning (you don’t have to be an expert on cutting edge neural network techniques, but you should be perfectly capable of curating data, fine-tuning a policy on that data and hypothesising potential mitigations when something doesn’t work). WHAT YOU’LL DO - Post-train manipulation policies via behaviour cloning and RL; own the full loop from data to deployment. - Come up with data preprocessing strategies to improve the quality of collected data. - Work with the simulation team to set up RL training using digital twin, and then iterate on reward and simulation quality to ensure successful transfer to the real world. - Partner with the data collection organization to drive data collection activities for a specific capability: specify what good data looks like, ensure diversity and coverage, and iterate on instructions. - Expand observation and action spaces with new components required to support novel capabilities, and work with the Teleoperations team to expose these components to robot operators. - Partner with Teleoperations and Controls teams to improve motion smoothness and teleoperation experience. - Interface with hardware design team to ensure that manipulation team findings regarding the current generation of hardware are reflected in future designs. WHAT WE'RE LOOKING FOR - 3+ years working on robots (industry or research) with shipped artifacts to show for it. A good understanding of modern teleoperation and low-level control stack. - Experience with neural network post-training. - Familiarity with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training, PyTorch or JAX. Ability to profile & debug numerics and write maintainable research code. - Good familiarity with modern software engineering practices. - Ability to document experiments clearly and communicate trade‑offs crisply. Nice to have: - Experience training VLA models for manipulation (autoregressive, diffusion or flow-matching based). Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open VLA frameworks. - Experience applying RL to robotics problems. - Publications at top-tier robotics or deep learning conferences or equivalent open‑source contributions. 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: US, Boston, MA 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 design robots in simulation before building them in hardware. As a Robotics Simulation & RL Engineer, you will help design and validate future generations of our robotic platforms - including bipedal and wheeled systems - using physics simulation and reinforcement learning. You will develop tools to determine whether a robot design can perform real-world tasks before committing to hardware. Your work will directly inform robot architecture, actuator selection, sensor placement, and control strategies. A key responsibility of this role is owning and validating the canonical robot models (URDF and simulation assets) used across simulation and control stacks. WHAT YOU’LL DO - Design and evaluate new robot platforms using physics simulation - Analyze robot capabilities including workspace, manipulability, dynamic balance, and torque limits - Use reinforcement learning to stress-test robot designs and explore capability limits - Own and maintain URDF models of current and future robot platforms - Maintain the CAD → URDF → simulation pipeline - Develop tools and benchmarks to evaluate locomotion, manipulation, and platform robustness - Provide quantitative feedback to hardware teams on actuator sizing, joint placement, mass distribution, and sensor layout - Collaborate with mechanical, control, and perception teams to guide platform design decisions WHAT WE'RE LOOKING FOR - M.Sc http://M.Sc. or Ph.D. in Robotics, Mechanical Engineering, Control, or a related field - Strong foundation in robot kinematics and dynamics - Experience with robot simulation environments (MuJoCo, Isaac Sim, Gazebo, or similar) - Experience with reinforcement learning in robotics or physics-based simulation - Experience working with URDF or similar robot description formats - Strong programming skills in Python and/or C++ - Experience training RL locomotion or manipulation policies Nice to have: - Experience with legged, humanoid, or wheeled robots; - Experience with whole-body control or torque-controlled robots; - Experience with simulation-driven hardware design; - Experience building large-scale RL training pipelines. WHAT WE OFFER - Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources. - Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays. - 401(k) retirement plan with a 4% employer match. - Equity included–we believe builders should share in what they build. - Free daily catered lunch, snacks, and drinks in‑office. - Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics. - Freedom to influence the product and own key initiatives. For this role in Massachusetts, the target base salary range is $200K–$300K USD per year; your placement in that range depends on how your experience maps to our internal leveling.

Location: Santa Clara, CA Workplace: onsite About Welo Data Welo Data, a Welo Global brand, is the multilingual data and evaluation partner for foundation labs and enterprises deploying GenAI systems globally. They deliver the human judgment, data infrastructure, and evaluation systems that ensure AI models perform reliably across languages, cultures, and real-world contexts, at every stage from training through deployment.  Its global network of 500,000+ vetted experts spans 300+ languages and locales, enabling high-quality multilingual data creation and structured model evaluation across the full spectrum of modern AI applications — from large language models and voice and speech systems to agentic workflows and robotics and embodied AI. This breadth of linguistic, cultural, and domain expertise enables Welo Data to address critical AI development challenges, including safety, bias, inclusivity, and cross-lingual reliability. A unified global operating model, led by specialized program and quality experts and grounded in assessment-driven talent selection, localized rubrics, and continuous calibration, ensures consistent performance across languages, domains, and modalities. Underpinning all of this is NIMO™ (Network Identity Management and Operations), Welo Data's proprietary identity and fraud-prevention framework. Built to maintain data integrity and workforce trust across a global contributor base, NIMO combines advanced verification, continuous monitoring, and structured QA to ensure every dataset is accurate, traceable, and culturally grounded. welodata.ai    Role Overview: We're hiring a Robotics Safety & Compliance Lead to own safety, risk, and compliance across our robotics operations — and to lead the function as it scales. This is a builder-leader role: you'll set the standard, establish the frameworks, and grow the program (and eventually the team) that keeps our labs and data collection environments safe, compliant, and audit-ready. You'll be the senior voice on safety in the room with operations, engineering, and EHS — setting direction rather than waiting for it, and building practical frameworks that support both speed and control. What You Will Do Own safety and compliance end to end across robotics labs and data collection environments. Set the safety strategy and roadmap as programs scale across sites, and define what "good" looks like for the function. Develop and implement safety standards, SOPs, and risk mitigation frameworks. Conduct risk assessments across different lab setups (humanoid, teleoperation, motion capture, etc.). Serve as the escalation point and decision-maker on safety risk — including the authority to pause work when conditions require it. Lead incident response processes, reporting, and root cause analysis. Conduct regular audits and maintain audit readiness across sites. Build and lead safety training, onboarding, and a safety champion network across lab teams. Influence senior stakeholders and report on safety posture, risk trends, and program maturity to leadership. Hire, mentor, and grow safety and compliance support as the program expands. Partner with engineering on safe system design — cell layout, e-stops, guarding, interlocks, and operating envelopes. Balance operational speed with safety and compliance requirements. What Good Looks Like Clear, practical safety frameworks that teams actually follow. A safety culture the is owned by the organization, not one that depends on one person policing it. Strong risk awareness without slowing down execution. High audit readiness and clean compliance posture. Proactive identification and mitigation of safety risks. Credibility with engineering — seen as a technical partner, not a gate. Strong partnership with operations and engineering teams. Basic Qualifications 5+ years of experience in safety, compliance, or EHS roles (technical or lab environments preferred). Demonstrated leadership experience — owning a program, leading cross-functional initiatives, or managing/mentoring others. Experience developing and implementing safety programs or frameworks from the ground up. Strong understanding of risk assessment and incident management. Ability to translate standards into practical, operational processes. Clear communication and proven ability to influence senior and technical stakeholders. Familiarity with safety standards (e.g., ISO frameworks such as ISO 10218, ISO/TS 15066, ANSI/RIA R15.06). Preferred Qualifications Experience in robotics, manufacturing, industrial, or lab-based environments. People management experience, or experience building a function and its first hires. Software or technical background as a plus — comfort with ROS, robot control software, teleoperation and motion capture systems, or scripting (e.g. Python) to analyze incident and sensor data. Experience building or automating compliance tooling — audit tracking, incident dashboards, or safety checklists integrated into lab workflows. Experience supporting high-growth or rapidly scaling operations. Background working with cross-functional technical teams. Work Environment and Physical Requirements Onsite lab environment (robotics lab, warehouse, or similar setup). Must be able to stand for extended periods during audits and inspections. Must be able to occasionally lift and/or move up to 50 lbs. Fast-paced environment with evolving operational needs. Why This Role Matters As robotics programs scale, safety and compliance become critical to sustainable operations. This role leads how we operate responsibly, reduce risk, and build systems that scale without compromising safety. Benefits Included in the Offer: - Friendly Working Environment - IT Equipment - Social Activities - Global Mobility Policy - Employee Referral Program - Employee Assistant Program - Medical, Dental, and Vision Insurance - HSA & FSA - 401(k) retirement - Short & Long Term Disability Insurance - Accident, Critical Illness, Hospital Indemnity Insurance  - Telemedicine Benefit - Annual Leave - Paid Public Holidays - Maternity/Paternity Leave   Hourly Pay: $65-$75/hr.   Job Reference: #LI-JC1

Location: Canada, Vancouver, BC 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 Senior Prototype Engineer to drive the development, assembly, integration, and validation of advanced humanoid robotic systems, with a particular focus on robotic hands, arms, end-effectors, and complex electromechanical mechanisms. This role combines deep hands-on engineering expertise with proven technical leadership and team management experience. You will take ownership of complex prototype development activities, guide engineering execution, and work closely with Mechanical, Electrical, Embedded Software, and Controls teams to transform innovative designs into reliable, high-performance robotic systems. We are looking for someone who has successfully led and developed technical teams, established efficient prototyping processes, and delivered complex hardware projects in fast-moving engineering environments. As our Vancouver robotics operations continue to grow, this position offers the opportunity to progress into a broader technical leadership role, helping shape our prototyping capabilities, engineering standards, and team development. Your work will directly influence the technical quality, development speed, and scalability of Humanoid's next-generation robotic platforms. WHAT MAKES THIS ROLE EXCITING - Take ownership of complex humanoid robot prototyping, including dexterous hands, arms, actuators, and advanced electromechanical assemblies. - Combine hands-on engineering with technical leadership, guiding complex prototype development from concept through validation. - Apply your previous team management and mentoring experience to strengthen engineering execution and build effective prototyping practices. - Solve challenging problems in robotic manipulation, precision actuation, sensor integration, and hardware-software interaction. - Collaborate with a multidisciplinary robotics team spanning mechanical, electrical, embedded software, and controls. - Play a key role in scaling Humanoid's prototyping capabilities, with potential to grow into a broader team leadership position. WHAT YOU’LL DO - Lead the development, assembly, integration, and commissioning of complex robotic prototypes, including hands, arms, end-effectors, actuators, sensors, and electromechanical subsystems. - Take ownership of prototype development from initial build through calibration, testing, debugging, validation, and design iteration. - Provide technical leadership and direction to engineers and technicians, helping establish priorities, resolve engineering challenges, and maintain execution quality. - Apply previous team management experience to mentor technical team members, develop capabilities, and establish effective engineering workflows. - Coordinate prototype development activities, ensuring clear technical priorities, efficient resource allocation, and alignment with engineering milestones. - Drive advanced hardware troubleshooting, root-cause analysis, and failure investigation across mechanical, electrical, and embedded systems. - Oversee the integration, calibration, and performance optimization of actuators, encoders, force/torque sensors, tactile sensors, and robotic control interfaces. - Partner with Mechanical, Electrical, Embedded Software, and Controls teams to identify design limitations, integration risks, and opportunities for performance improvement. - Lead and contribute to technical design reviews, providing practical engineering feedback on assembly, reliability, serviceability, and manufacturability. - Establish and improve prototype assembly procedures, integration workflows, testing methodologies, and validation standards. - Drive rapid prototyping and engineering iteration, ensuring timely resolution of technical blockers and efficient development cycles. - Support system-level testing, performance characterization, reliability assessments, and prototype-to-production transitions. - Develop and maintain technical documentation, including assembly instructions, test procedures, troubleshooting guides, SOPs, and engineering reports. - Collaborate with engineering and program leadership to plan prototype builds, track technical progress, manage risks, and communicate development priorities. - Work closely with teams across Vancouver, London, and Boston, supporting cross-site integration and technical collaboration. - Promote a safe, organized, and efficient prototyping environment, maintaining appropriate tools, equipment, and engineering practices. WE’RE LOOKING FOR - 10+ years of professional experience in robotics prototyping, mechatronics, electromechanical integration, or advanced robotic hardware development. - 5+ years of proven track record directing technician groups within a dynamic research and development setting. - Demonstrated experience mentoring, developing, and coordinating technical team members, with the ability to establish priorities and drive engineering execution. - Bachelor's or Master's degree in Robotics, Mechatronics, Mechanical Engineering, Electrical Engineering, or a related technical discipline, or equivalent practical engineering experience. - Strong hands-on experience building, integrating, testing, and troubleshooting complex robotic or electromechanical systems. - Proven track record of taking complex hardware prototypes from concept through integration, commissioning, validation, and delivery. - Deep understanding of precision mechanical assemblies, actuators, motors, sensors, wiring, and embedded hardware interfaces. - Experience with fine-pitch soldering, precision wiring, cable assemblies, connectors, and electrical integration. - Strong knowledge of actuator commissioning, sensor calibration, motor control interfaces, and robotic system testing. - Ability to interpret mechanical drawings, electrical schematics, wiring diagrams, and engineering documentation. - Experience using laboratory and diagnostic equipment, including oscilloscopes, multimeters, power supplies, and precision measurement instruments. - Demonstrated ability to lead complex troubleshooting, root-cause analysis, and engineering problem-solving activities. - Experience establishing or improving prototype assembly, integration, testing, and validation processes. - Strong project coordination skills, including technical planning, resource prioritization, risk management, and cross-functional execution. - Excellent communication skills, with the ability to collaborate effectively with engineering teams, technical leadership, and program stakeholders. - Ability to balance hands-on technical involvement with broader engineering leadership responsibilities in a fast-paced R&D environment. BONUS QUALIFICATIONS - Experience developing humanoid robots, dexterous robotic hands, robotic arms, or advanced manipulation systems. - Previous experience building, scaling, or managing a robotics prototyping, integration, or hardware development team. - Experience with multi-DoF robotic mechanisms, precision actuators, transmissions, and complex joint assemblies. - Experience with tactile sensors, force/torque sensors, encoders, IMUs, and robotic sensing technologies. - Knowledge of motor control systems, drive tuning, actuator performance analysis, EtherCAT, or CAN communication protocols. - Experience with rapid prototyping and fabrication, including FDM/SLA 3D printing, CNC machining, and laser cutting. - Familiarity with SolidWorks or similar CAD tools and the ability to perform mechanical design modifications. - Experience using Python, ROS/ROS2, or other tools for robotic hardware testing, calibration, or automation. - Experience developing automated test setups, hardware validation infrastructure, or data acquisition systems. - Experience supporting hardware NPI, prototype-to-production transitions, or low-volume robotic manufacturing. - Background in robotics, autonomous systems, aerospace, automotive, or advanced hardware startups. WHAT WE OFFER - Comprehensive extended health benefits starting on your first day, including fully paid medical and dental, virtual care, employee and family assistance, and worldwide emergency medical support. - Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays. - Paid end-of-year shutdown: annual company-wide holiday closure spanning Christmas through New Year’s Day. - Competitive equity: stock options with meaningful upside as we scale. - Free daily catered lunch, snacks, and drinks in‑office. - Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics. - Freedom to influence the product and own key initiatives.