Robotics Systems Engineer, Physical AI

About us

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