Senior Machine Learning Engineer, Perception - Autonomous Driving

Nvidia • Santa Clara, CA

88d • $184,000 - $287,500

About The Position

We are looking for a Machine Learning Engineer to join our Autonomous Vehicle Perception team. In this role, you will help build perception modules that enable static world understanding without HD Map— including road layouts, lane structures, boundaries, crosswalks, and other traffic components critical for driving without reliance on HD maps. Your models must scale across continents, adapt to diverse road systems, and handle corner case scenarios towards meeting the highest standards of safety and reliability.

Requirements

• MS or PhD in Computer Science, Engineering, or related field (focus on Deep Learning, AI, or similar), or equivalent experience.
• 8+ years of experience applying ML/DL to real-world perception problems.
• Strong Python programming skills with proven software engineering practices.
• Hands-on experience with deep neural network training, inference, and optimization using PyTorch, TensorRT (or similar).
• Solid understanding of the mathematical foundations of ML/DL.
• Proven experience in data-driven analysis: setting up metrics, running large-scale experiments, interpreting results, and applying insights to guide model improvements.
• Experience developing scalable software for large, sophisticated systems.
• Excellent interpersonal skills; able to collaborate optimally across teams.
• Self-motivated, analytical, and eager to solve meaningful and challenging perception problems.

Nice To Haves

• Proficiency in crafting perception systems that extend globally and adapt to different traffic environments.
• Strong background in data analytics, error analysis, and metric-driven iteration for ML systems.
• Proven track record to address rare and long-tail scenarios, from unusual road markings to sophisticated intersections.
• Hands-on work with lane detection, road boundaries, crosswalks, and similar tasks.
• Expertise with Transformers, BEV architectures, and modern static-world perception techniques.

Responsibilities

• Collaborate with researchers and engineers to transform innovative algorithms into production-ready perception modules.
• Research and prototype deep learning methods for lane graph construction, road boundary detection, traffic element recognition, and other static-world tasks.
• Develop and implement experiments at scale, applying detailed analytics to validate adaptability and improve generalization to rare and corner-case scenarios.
• Drive end-to-end deployment of perception models — from prototyping and validation to integration, optimization, and delivery into the autonomous driving stack.

Benefits

• Equity and benefits package.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Industry: Computer and Electronic Product Manufacturing
• Education Level: Master's degree