Autonomy Bringup Engineer

Polymath Robotics; San Francisco (CA); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Hybrid workplace SF Mission office

Open source advocacy

Job summary

Polymath Robotics is seeking a hands-on robotics software engineer to join our SF Mission Office. You will own end-to-end bringup across simulation, bench, and on-vehicle phases, working with perception, controls, navigation, and ROS2 architectures.

You’ll partner with clients and integrators, diagnose complex issues from logs and ROS bags, and help scale successful patterns across multiple vehicles while staying pragmatic and customer-focused.

Qualifications

• Hands-on experience with robots or autonomous systems.
• Evidence you automated or systematized a manual process before.
• Strong remote debugging skills using logs, ROS bags, and remote sessions.
• Able to explain system capabilities and limitations to clients and integrators.
• Excellent written communication for test coverage, handoff criteria, and proposals.

Responsibilities

• Own vehicle bringup end-to-end across simulation, bench, and on-vehicle phases.
• Build and extend automated test suites that auto-generate issues on failure.
• Identify reusable patterns and scale them across multiple vehicles.
• Support integrators and customers on-site and remotely during testing phases.
• Communicate with clients and integrators to align on requirements and proposals.
• Contribute to ROS2 architecture to fix gaps and reduce recurring manual steps.
• Travel as needed for sales meetings and on-site support.

Skills

C++

Python

ROS/ROS2

Systems architecture

Test automation

Remote debugging

Client communication

Documentation

Job description

Polymath Robotics is seeking a hands-on robotics software engineer to join our SF Mission Office. You will own end-to-end bringup across simulation, bench, and on-vehicle phases, working with perception, controls, navigation, and ROS2 architectures.

You’ll partner with clients and integrators, diagnose complex issues from logs and ROS bags, and help scale successful patterns across multiple vehicles while staying pragmatic and customer-focused.