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Robotics Systems Engineer

Stealth Startup
San Francisco, USA
Full Time, Contract
Mid
Onsite
USD 40-45 hourly / hour
Discovered 1 weeks ago
LinuxGitPythonC++ROSROS 2
Free

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About Us

We are a well-capitalized stealth startup building robotic foundation models and world models for Physical AI. Founded by researchers from leading AI labs, our team works across robot hardware, data, infrastructure, and machine learning.

The Role

We are looking for a hands-on Robotics Systems Engineer to build and operate the robotic platforms behind our research.

You will work across hardware, embedded systems, robot software, communications, calibration, data collection, evaluation, and deployment. This role is broader than mechatronics: you should be comfortable debugging the complete system, from sensors and actuators, close loop control, and learned-policy evaluation.

Responsibilities

  • Bring up, integrate, and maintain humanoids, robotic arms, and custom platforms.
  • Debug mechanical, electrical, networking, communication, and software failures.
  • Integrate and help design sensors, actuators, motor controllers, embedded devices, compute, wiring, and power systems.
  • Develop robot drivers, hardware interfaces, diagnostics, and automation in Python or C++.
  • Build distributed robotics software using ROS, ROS 2, ZMQ, and related technologies.
  • Maintain teleoperation, robot data collection, dataset validation, and policy-evaluation software.
  • Perform calibration, functional testing, reliability testing, and performance characterization.
  • Develop logging, monitoring, health checks, and fault-recovery tools.
  • Work with ML researchers to deploy and evaluate learned policies on physical robots.
  • Improve system reliability, performance, safety, and maintainability.
  • Use AI coding agents to accelerate implementation, testing, debugging, and documentation.

Qualifications

  • BS or MS in Robotics, Computer Engineering, Electrical Engineering, Mechanical Engineering, Mechatronics, Computer Science, or a related field.
  • Experience integrating or operating complete robotic systems.
  • Proficiency with Linux, Git, and Python or C++.
  • Familiarity with ROS, ROS2, ZMQ or similar communication frameworks.
  • Familiarity with sensors, actuators, embedded electronics, networking, and robot system design.
  • Understanding of robot-learning workflows and their hardware and electronics requirements.
  • Experience with robot data collection or evaluation software.
  • Strong cross-stack debugging and problem-solving skills.
  • Experience using AI coding agents such as Claude Code, Codex, or comparable tools, including reviewing and validating generated code.
  • Comfortable working in a fast-moving environment and taking ownership of ambiguous problems.

Nice to Have

Experience with humanoids, manipulators, quadrupeds, or mobile robots.

Experience with teleoperation or learned-policy deployment.

Familiarity with CAN, EtherCAT, DDS, SPI, UART, or real-time systems.

Embedded programming experience with STM32, ESP32, Raspberry Pi, Jetson, or similar platforms.

Experience with camera, tactile, force-torque, encoder, or IMU integration and calibration.

Familiarity with multimodal data synchronization, experiment tracking, and robotics evaluation metrics.

CAD, machining, wiring, soldering, or rapid-prototyping experience.

What You Will Gain

Build advanced robots alongside experienced AI researchers and roboticists.

Work across the complete robot-learning stack, from hardware to foundation models.

Help shape the systems and engineering practices of an early-stage robotics company.

Hiring Process

Introductory conversation

Technical interview

One-day on-site assessment (paid at $40/hr).

Initial six-month contract with strong potential for a longer-term opportunity.

Logistics & Benefits

  • Location: San Francisco, CA (South Beach/SoMa) — on-site 5 days a week
  • Schedule: Full-time, 40 hours/week, including a 30-minute lunch break
  • Employment: W-2, facilitated through Hire.io
  • Compensation: $40+/hour, negotiable based on experience

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