Senior Software Engineer - Autonomous Vehicles

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Senior Software Engineer for Autonomous Vehicles at NVIDIA, focusing on integrating ML and classical trajectory planners within a safety-oriented framework for SAE Level 3/4 autonomy. The role involves architectural work, establishing safety frameworks, building minimum-risk planning, and designing scalable architectures for self-driving products.

What you'd actually do

  1. Various architectural work cross team–classical planner and machine learning planner.
  2. Establish the framework where safety requirements are satisfied in trajectory planning.
  3. Build Minimum-Risk-Planning in a high level autonomy system.
  4. Establish scalable architecture for various Nvidia self driving stack as a product
  5. Actively engaged in planning and control algorithms development and implementation. Understand the SW architecture,

Skills

Required

  • 12+ years of relevant industry experience.
  • A track record of driving a large size of self driving projects through the entire development lifecycle.
  • BS/MS or higher or equivalent experience in robotics, computer science, or related engineering fields.
  • Experience in agile SW development process and delivering SW as a product, preferably in safety-critical applications. Ability to design for reliability and testability.
  • Strong software engineering fundamentals.
  • Excellent verbal and communication skills.
  • Strong analysis skills.

Nice to have

  • Technically leading the deliverable in a large scale of self driving feature
  • Exceptional SW Engineering skill and experience
  • Passion for innovative technology and actively stays informed on leading technologies and trends, especially in the field of autonomous vehicles and autonomous systems.
  • Be hands-on and work well with cross-team, with a significant level of detail orientation and a penchant for data organization and willing to firefight.

What the JD emphasized

  • safety-oriented framework
  • safety requirements are satisfied
  • Safety related work experience
  • safety-critical applications
  • large size of self driving projects
  • large scale of self driving feature

Other signals

  • integrating both machine learning and classical trajectory planner
  • safety-oriented framework in high autonomy level
  • behavior planning, trajectory planning, Safety concept and machine learning overall
  • Establish scalable architecture for various Nvidia self driving stack as a product