Software Engineer, Autonomous Systems
H
Humble RoboticsAutonomous Vehicles
RemoteFull-Time
SalaryThis role is eligible for base salary + benefits + equity compensation.
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Job Details
- Required Skills
- Embedded SystemsC++RustCI/CDLinux
Requirements
- BS or MS in Computer Science, Electrical Engineering, Robotics, or a related field—or equivalent industry experience
- Strong proficiency in Rust or C++ with experience shipping low-latency, concurrent software on Linux
- Familiarity with real-time scheduling, inter-process communication, synchronization primitives, and debugging latency-sensitive concurrent systems
- Experience contributing to Linux systems software, hardware-adjacent infrastructure, sensor / compute platform bring-up, or similarly close-to-hardware systems
- Experience contributing to software for autonomous vehicles, mobile robots, or other safety-critical systems
- Hands-on work with sensor integration
- Experience with GPU-accelerated compute or productionizing AI models
- Experience with low-latency IPC, shared-memory transport, or high-throughput pub-sub systems
- Experience with Bazel or other hermetic build systems
- Experience with cross-compilation, packaging, or deployment for Linux-based systems
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
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