Senior Software Engineer, Onboard Autonomy

What You’ll Do

• Develop, integrate, and deploy onboard autonomy behaviors (e.g., navigation, obstacle avoidance, lane/route following, docking, interaction behaviors).
• Implement and maintain real-time decision-making components: behavior planning, state machines/behavior trees, local planning, and control interfaces.
• Build robust sensor-driven autonomy pipelines on-device (camera, lidar, radar, IMU, wheel odometry, GNSS), including synchronization, calibration hooks, and fault handling.
• Optimize autonomy performance for latency, CPU/GPU usage, memory, and power on embedded compute (e.g., NVIDIA Jetson, x86 edge boxes, custom ECUs).
• Design and implement safety and fallback strategies: health monitoring, degraded modes, watchdogs, safe-stop, and redundancy-aware logic.
• Own the autonomy stack’s on-robot integration: bring-up, debugging, profiling, logging, and release validation on real hardware.
• Improve onboard observability: structured logs, traces, metrics, event recording, and tools to support incident review and rapid iteration.
• Collaborate with perception, mapping/localization, controls, hardware, and systems teams to define clear interfaces and ship end-to-end features.
• Participate in field testing and root-cause analysis of autonomy issues seen in real deployments.

Required Experience

• 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 (embedded Linux, real-time-ish systems, performance-sensitive code).
• Understanding of autonomy fundamentals: planning, state estimation/localization, controls, and how they interface (you don’t need to be an expert in all).
• Experience with robotics middleware and tooling (commonly ROS/ROS 2, custom pub/sub frameworks, gRPC, DDS, etc.).
• Proficiency with debugging and performance tools (e.g., gdb/lldb, perf, flamegraphs, profiling GPU workloads, log/trace analysis).
• Strong testing discipline: unit/integration tests, simulation/HIL concepts, and safe rollout practices for autonomy.

Nice to Have

• Experience with behavior trees (e.g., BehaviorTree.CPP), hierarchical state machines, or mission/task planning.
• Practical experience with local planners (trajectory rollout, MPC, sampling-based methods) and real-time control loops.
• Sensor fusion experience (EKF/UKF), time sync, calibration, and handling intermittent sensors.
• Experience with mapping and localization stacks (scan matching, visual-inertial odometry, SLAM, map-based localization).
• Familiarity with safety standards/processes (e.g., ISO 26262 concepts, FMEA, hazard analysis) depending on domain.
• Experience deploying autonomy to fleets: OTA updates, versioning, configuration management, and field telemetry.
• Experience in inference optimization

Compensation: $193,930 - $291,150/year base pay, plus annual performance bonus, equity, and competitive benefits.