Senior Perception Engineer - Autonomous Vehicles

Details

Intelligent machines powered by artificial intelligence computers that can learn, reason, and interact with people are no longer science fiction. GPU deep learning provides the foundation for machines to learn, perceive, reason, and solve problems. NVIDIA's GPUs run deep learning algorithms that simulate human intelligence and act as the brains of computers, robots, and self-driving cars that can perceive and understand the world.

NVIDIA is looking for a Senior Perception Engineer to develop and productize autonomous driving solutions. As a member of the perception team, you will build 3D obstacle perception solutions based on multi-sensor fusion, including cameras, ultrasonic sensors, and radar, to estimate high-resolution reconstructions of the world. The primary approach will be deep learning, with a focus on improving solution robustness, accuracy, and efficiency to enable autonomous driving anywhere and anytime.

Responsibilities

• Develop multi-sensor-fusion-based deep learning models for obstacle perception and fusion in complex driving environments.
• Conduct applied research and development of innovative deep learning and multi-sensor fusion algorithms to improve the accuracy of 3D obstacle perception solutions under challenging and diverse scenarios.
• Identify and analyze the strengths and weaknesses of 3D obstacle perception solutions using large-scale benchmark data, including real and synthetic data.
• Improve solutions iteratively through KPI development and optimization, including data verification, model architecture design, loss function engineering, and detailed machine learning debugging.
• Productize 3D obstacle perception solutions by meeting requirements for safety, latency, and software robustness, with a strong emphasis on production deep learning model development.
• Drive and prioritize data-driven development in collaboration with large data collection and labeling teams.
• Prioritize data collection and labeling to maximize the value of data for improving perception system accuracy.

Requirements

• 10+ years of hands-on experience developing deep learning and algorithms to solve sophisticated real-world problems.
• Proficiency with deep learning frameworks such as PyTorch.
• Experience with multi-sensor fusion using cameras, ultrasonic sensors, and radar for perception tasks, particularly high-resolution world reconstruction.
• Proven experience developing production deep learning models, including data verification, model architecture design, loss function engineering, and machine learning model debugging.
• Experience with data-driven development and collaboration with data and ground-truth teams.
• Strong programming skills in Python and/or C++.
• Outstanding communication and teamwork skills.
• BS, MS, or PhD in computer science, electrical engineering, sciences, or a related field, or equivalent experience.

Preferred Qualifications

• Experience with end-to-end deep learning model development.
• Expertise developing perception solutions for autonomous driving or robotics using deep learning with multi-sensor input.
• Hands-on experience developing and deploying DNN-based solutions to embedded platforms for real-time applications.
• Good understanding of 3D computer vision fundamentals, camera calibration—including intrinsic and extrinsic calibration—and sensor fusion principles.
• Experience developing in CUDA and implementing CUDA kernels as part of training or inference pipelines.

Compensation and Benefits

The base salary is determined by location, experience, and the pay of employees in similar positions. The base salary ranges are USD 184,000–287,500 for Level 4 and USD 224,000–356,500 for Level 5. The role is also eligible for equity and benefits.

Applications will be accepted at least until July 12, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.