Senior/Staff Software Engineer (Machine Learning Runtime), Motion Planning

Job description

Job responsibilities

• Design, implement, and optimize the production runtime pipeline for ML-based autonomous vehicle planning.
• Integrate machine learning models into a scalable, safety-critical planning software stack.
• Optimize end-to-end inference performance through algorithm optimization, C++ implementation, profiling, memory optimization, and efficient execution on compute-constrained embedded platforms.
• Develop high-performance C++ components for feature extraction, inference, post-processing, trajectory generation, and runtime orchestration.
• Design runtime validation, safety guardrails, and fallback mechanisms to ensure generated trajectories are feasible, robust, and compliant with traffic rules.
• Investigate complex runtime issues by tracing failures across the planning pipeline, from feature extraction through inference to trajectory generation.
• Debug difficult edge-case scenarios using logs, profiling tools, visualization, offline replay, and quantitative analysis to identify root causes and implement robust solutions.
• Build tooling and infrastructure to improve debugging, observability, performance analysis, testing, and runtime monitoring.

Job requirements

• BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, or a related field.
• 4+ years of experience developing high-performance production software.
• Strong C++ programming skills with experience building, optimizing, and maintaining large-scale software systems.
• Experience optimizing real-time systems, including latency, throughput, memory usage, and multithreaded performance.
• Experience deploying machine learning inference into production environments.
• Familiarity with TensorRT, CUDA, ONNX Runtime, or similar inference acceleration frameworks.
• Strong software engineering fundamentals, including software architecture, testing, and code quality.
• Excellent debugging and analytical problem-solving skills, with the ability to systematically investigate complex software and system-level issues.