Software Engineer, Autonomous Systems

Additional Information As part of the interview process, we may use Artificial Intelligence (AI) tools to compare your qualifications and experience to the job description. A human reviews all AI output and makes a final hiring decision. Humble Robotics does not rely on the output to make any employment decisions. Some applicants may have a legal right to opt-out of the use of AI as part of our interview process. Contact legal@humblerobotics.ai to exercise this right or if you have further questions on the use of AI tools in our hiring process. Humble Robotics is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, national origin, gender, age, religion, disability, sexual orientation, veteran status, marital status or any other characteristics protected by law. Humble Robotics will consider qualified applicants with arrest and conviction records in a manner consistent with local ordinances.

Position Overview

We're looking for a software engineer to help build the software systems that make our autonomous trucks drive. Your primary focus will be on software that runs on the vehicle, and you'll contribute across the stack—from sensors and inference to developer tooling and fleet-facing systems—working closely with teammates across robotics, ML, and controls. We also value engineers who are excited to jump into adjacent parts of the stack as needed, from firmware-facing integrations and developer tooling to cloud services and internal applications. This is a chance to support a production autonomy stack from day one, shipping code that runs on real trucks hauling real freight.

Key Responsibilities

Contribute to the design, implementation, and optimization of software across the autonomy stack, with an emphasis on real-time systems running on the vehicle

Help build and improve on-vehicle data logging and recording systems

Contribute to the hermetic build and cross-compilation pipeline, including packaging and deployment for on-vehicle compute platforms and adjacent system components

Instrument, profile, and improve system performance end-to-end—from IPC latency to compute throughput to disk I/O

Write tests and support CI improvements to ensure system reliability

Contribute to integrations across on-vehicle, cloud, and fleet-facing systems—remote data pipelines, over-the-air updates, and connectivity

Jump into adjacent engineering work as needed, from firmware-facing integrations and developer tooling to cloud services and internal web applications

Collaborate with ML and controls engineers to integrate their work into the real-time on-vehicle stack

Minimum Qualifications

Preferred Qualifications

Compensation