Title: Robotics R&D Engineer III
Req ID:
Location: Redmond, WA
Schedule: Core hours, + or - 10-3. Free breakfast and lunch every day on site
PR: $70-77/hr
Start Date: ASAP
Duration: 12 months + extensions up to 2.5 years
Day to Day:
As a Robotics R&D Engineer, you’ll run and iterate on experiments using real robotic systems, particularly manipulation platforms like robot arms, grippers, and dexterous hands. Day to day, you’ll develop and debug ROS-based software (ROS1/ROS2) while working in Linux to troubleshoot systems and keep robots running. You’ll rapidly prototype by testing, breaking, and refining both hardware and software in real time, while integrating sensors, actuators, and embedded components. You’ll also support lab operations including setup and basic networking, and collaborate with the team through Git and GitHub workflows to ensure experiments are reliable and scalable.
Key Responsibilities:
- Develop and maintain the robot software stack (ROS ecosystem)
- Execute and troubleshoot robot experiments on hardware and cluster environments
- Own lab setup and tooling (equipment ordering, setup, maintenance)
- Support system administration tasks:
- Linux machines
- networking (bandwidth, latency, connectivity)
- compute infrastructure
- Integrate and debug robot systems across hardware + software layers
- Contribute to Git-based development workflows and CI/CD pipelines
- Present updates, experiment results, and designs in team settings
Must Haves:
- Bachelor’s degree in Computer Engineering, Robotics Engineering, Computer Science, or related field
- Strong experience working in Linux environments (command line, terminals, system-level troubleshooting)
- Hands-on experience with real robotic hardware (not simulation-only)
- Proficiency with ROS (ROS1 and/or ROS2) and robotics software development
- Strong programming skills in Python and/or C++
- Experience with Git-based version control
Plusses:
- Experience working with robotic manipulation systems (robot arms, grippers, dexterous hands)
- Experience working with capture systems
- Experience with deep learning / perception models (training or deployment)
- Familiarity with CI/CD pipelines and GitHub workflows