Role Overview

We are seeking a Staff Software Engineer to support the auto-parking and low-speed autonomy stack. This role focuses on trajectory optimization, path smoothing, and local planning, with direct impact on parking features such as Auto Park, Summon, and Park-to-Park. The ideal candidate will combine strong algorithmic foundations with production-grade software execution, driving both system performance and scalability. This role is based in Newark, CA. and requires employees to be onsite five days a week.

Key Responsibilities:

• Motion Planning & Trajectory Optimization
  • Develop and enhance trajectory optimization algorithms (e.g., iLQR / MPC-based approaches) for low-speed scenarios
  • Design and implement constraint-aware optimization, including
  • Improve local planners to generate control-friendly trajectories
• System Architecture & Performance Optimization
  • Refactor and scale planning stack architecture for maintainability and extensibility
  • Optimize CPU usage and explore parallel/GPU acceleration opportunities
  • Improve system-level behaviors such as:
    • Stability under dynamic constraints
    • Scalability across scenarios and vehicle platforms
• Debugging, Validation, and Production Integration
  • Investigate and resolve real-world issues such as: Curvature discontinuities, velocity/trajectory mismatches, and edge-case steering behavior
  • Validate solutions using:
    • Simulation and vehicle logs
    • Multi-scenario testing and benchmarking
• Research, Prototyping, and Innovation
  • Evaluate and prototype new approaches (e.g., learned models, barrier functions, ML-based planning)
  • Benchmark and compare planning algorithms for production viability
  • Contribute to next-gen planning initiatives, including ML-driven planning
• Cross-Team Collaboration & Knowledge Transfer
  • Drive technical discussions and share algorithm insights across teams
  • Maintain high-quality documentation and support knowledge transfer
  • Track work via Jira with clear metrics and reproducible results

Required Qualifications:

• M.S. or Ph.D. in Robotics, Control, Electrical Engineering, or related field
• 5-8+ years of software development experience in autonomous driving, ADAS, or robotics, with a focus on large-scale data and real-time systems
• Strong programming skills in C/C++ with solid understanding of software engineering design principles and best practices
• Proven track record of delivering ADAS/AD features through the full production lifecycle: requirements analysis, architecture/design, implementation, unit testing, feature tuning, SIL/HIL validation, and in-vehicle deployment
• Hands-on experience with software integration on embedded platforms (e.g., NVIDIA Xavier/Orin, Infineon Aurix)
• Demonstrated ability to build reliable production-grade systems, including large-scale architectures, evaluation pipelines, and performance-optimized models
• Leadership experience

Preferred Qualifications:

• ML-based planning approaches
• GPU or parallel computing for planning
• Track record of production deployment in real vehicles