Robotics Systems Engineer, Physical AI

About us Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more. We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator. The role We're building a robotics data collection operation from scratch — and we need someone to figure out how to make it work. There's no playbook. No inherited infrastructure. No one to tell you what to do next. You'll own the entire stack: robot arms, sensors, VR teleoperation rigs, data pipelines, quality systems, and customer delivery. We currently operate leader-follower teleoperation setups and are actively building toward VR-based interfaces for higher-fidelity remote collection. You'll help us make that transition and define what the pipeline looks like at the other end. This is a 0-to-1 role. If you need clear instructions and a defined scope, this isn't for you. If you get energized by building something from nothing, keep reading. What you'll do - - Build the hardware infrastructure — Set up and maintain robot arms, cameras, and VR teleoperation rigs. Design workstation layouts. Keep systems calibrated. When something breaks mid-shift, get us back online. When we scale from 10 to 50 stations, figure out how - Build the data pipeline — Ingest multi-modal sensor streams (joint states, wrist and scene cameras, gripper, 6DOF controller poses), synchronize across modalities, validate quality, and export in formats customers need — LeRobot HDF5, RLDS, MCAP, ROSBAGS and custom specs. Own the full journey from sensor to deliverable dataset - Maintain edge infrastructure — Run local buffering and automated upload at capture facilities. Keep data flowing reliably from the floor to the cloud even when connectivity is flaky - Operationalize annotation tooling — Work with our ML team to run VLM/VLA-based annotation passes that auto-generate action labels from raw robot video. Own throughput, prompt reliability, and output validation. - Solve problems as they come — Debug hardware failures, adapt to new customer requirements, work around sensors that don't behave as expected. Document what you learn so we don't hit the same wall twice - Shape what comes next — Help us figure out when to specialize, what to build vs. buy, and how to scale globally Who we're looking for - - You've built something from scratch before — a lab setup, a data collection system, a side project, a startup — and you loved the ambiguity - You default to action — when you don't know the answer, you run an experiment instead of waiting for direction - You'd rather ship something imperfect and iterate than wait for perfect requirements - You take ownership end-to-end, even when it's outside your "job description" Experience requirements - - Hands-on experience with robotics, automation, or mechatronic systems — robot arms, drones, CNC machines, or something you built yourself - Proficiency in Python and experience building data pipelines from scratch - Comfortable in Linux and ROS/ROS 2, with the ability to pick up new tools quickly (Docker, cloud infra, whatever's needed) - Strong understanding of what makes a robot episode good training data — not just that it recorded, but that it's actually usable for imitation learning - Experience with multi-modal timestamp synchronization — hardware triggers, PTP, or software alignment across cameras and joint encoders Would be a plus: - Experience with VR-based teleoperation (e.g., Quest + ROS bridge, custom motion or haptic interfaces) - Familiarity with VLA training pipelines — OpenVLA, π0, GR00T N1, SmolVLA, or similar - You've worked with MCAP, rosbags, or other robotics data container formats - You've shipped something in a previous startup or early-stage environment - You have a GitHub, blog, or portfolio that shows what you've built Why Encord - - Competitive salary, commission, and meaningful equity in a high-growth startup - Clear, accelerated growth opportunities as the company scales rapidly - Strong in-person culture: 4 days/week in our newly launched North Beach loft office - Flexible PTO to fully recharge - 18 paid vacation days in the U.S. plus federal holidays - Annual learning & development budget - Comprehensive health, dental, and vision coverage - Frequent travel opportunities across the U.S., London, and Europe - Bi-annual company offsites, twice-weekly team lunches, and monthly socials