Job Description
An Autonomy Engineer at Nuro is responsible for developing and deploying real-time onboard autonomy software for self-driving vehicles, focusing on navigation, obstacle avoidance, sensor integration, safety strategies, and system optimization to enable safe and reliable autonomous operation.
Key Responsibilities
- Develop, integrate, and deploy onboard autonomy behaviors such as navigation, obstacle avoidance, lane following, docking, and interaction behaviors.
- Implement and maintain real-time decision-making components including behavior planning, state machines, local planning, and control interfaces.
- Build and optimize sensor-driven autonomy pipelines using onboard sensors like cameras, lidar, radar, IMU, wheel odometry, and GNSS.
- Optimize autonomy performance for latency, CPU/GPU usage, memory, and power on embedded compute platforms.
- Design and implement safety and fallback strategies, including health monitoring, degraded modes, watchdogs, safe-stop, and redundancy logic.
- Manage on-robot integration, debugging, profiling, logging, and validation of the autonomy stack on real hardware.
- Enhance onboard observability through structured logs, traces, metrics, and incident review tools.
- Collaborate with perception, mapping, localization, controls, hardware, and systems teams to define interfaces and ship end-to-end features.
- Participate in field testing and root-cause analysis of autonomy issues in real-world deployments.
Requirements
- Strong software engineering skills in C and/or Rust; Python acceptable as a supporting language.
- Experience shipping software that runs on-device with real-world constraints, including embedded Linux, real-time-ish systems, and performance-sensitive code.
- Understanding of autonomy fundamentals such as planning, state estimation, localization, and controls, with the ability to interface these components (expertise in all not required).
- Experience with robotics middleware and tooling commonly used in robotics, such as ROS, ROS 2, custom pub/sub frameworks, gRPC, DDS, etc.
- Proficiency with debugging and performance analysis tools, including gdb, lldb, perf, flamegraphs, profiling GPU workloads, and log trace analysis.
- Strong testing discipline, including experience with unit and integration tests, simulation, Hardware-in-the-Loop (HIL) concepts, and safe rollout practices for autonomy.
- Experience developing and deploying onboard autonomy behaviors such as navigation, obstacle avoidance, lane route following, docking, and interaction behaviors.
- Experience implementing and maintaining real-time decision-making components such as behavior planning, state machines, behavior trees, local planning, and control interfaces.
- Experience building sensor-driven autonomy pipelines on-device, including synchronization, calibration, fault handling, and integration of sensors such as camera, lidar, radar, IMU, wheel odometry, and GNSS.
- Experience optimizing autonomy performance for latency, CPU/GPU usage, memory, and power on embedded compute platforms such as NVIDIA Jetson, x86 edge boxes, or custom ECUs.
- Experience designing and implementing safety and fallback strategies, including health monitoring, degraded modes, watchdogs, safe-stop, and redundancy-aware logic.
- Experience owning the autonomy stack's on-robot integration, including bring-up, debugging, profiling, logging, and release validation on real hardware.
- Experience improving onboard observability through structured logs, traces, metrics, event recording, and tools to support incident review and rapid iteration.
- Ability to collaborate with perception, mapping, localization, controls, hardware, and systems teams to define clear interfaces and ship end-to-end features.
- Participation in field testing and root-cause analysis of autonomy issues observed in real deployments.
Benefits & Perks
Compensation/salary range between $193,930 and $291,150 per year
Annual performance bonus
Equity
Competitive benefits package
Ready to Apply?
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