Senior Perception Engineer - Autonomous Vehicles

Details

Intelligent machines powered by Artificial Intelligence 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, simulating human intelligence, and act as the brain of computers, robots and self-driving cars that can perceive and understand the world.

As a member of the perception team you will develop and productize NVIDIA's autonomous driving solutions. You will work on building world-class 3D obstacle perception solutions based on multi-sensor fusion (cameras, ultrasonic sensors, radar) to estimate high-resolution reconstructions of the world. The primary approach is deep learning with emphasis on 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 R&D of innovative deep learning and multi-sensor fusion algorithms to improve output accuracy of 3D obstacle perception under challenging and diverse scenarios.
• Identify and analyze strengths and weaknesses of 3D obstacle perception solutions using large-scale benchmark data (real and synthetic); iteratively improve models through KPI building and optimization, careful data verification, model architecture design, loss function engineering, and detailed ML bug-fixing.
• Productize developed 3D obstacle perception solutions to meet product requirements for safety, latency, and software robustness, with a strong emphasis on production deep learning model development.
• Drive and prioritize data-driven development by working with large data collection and labeling teams to prioritize high-value data, plan data collection, and prioritize labeling to maximize data value.

Requirements

• 10+ years of hands-on experience developing deep learning algorithms to solve sophisticated real-world problems; proficiency with deep learning frameworks (e.g., PyTorch).
• Experience in multi-sensor fusion (cameras, ultrasonic sensors, radar) for perception tasks, particularly for high-resolution world reconstruction.
• Proven experience in production deep learning model development, including data verification, model architecture design, loss function engineering, and debugging ML models.
• Experience in 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/PhD in Computer Science, Electrical Engineering, sciences, or related fields (or equivalent experience).

Ways to stand out

• Experience on end-to-end deep learning model development.
• Proven expertise in 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 fundamentals of 3D computer vision, camera calibrations (intrinsic and extrinsic), and sensor fusion principles.
• Experience with CUDA and ability to implement CUDA kernels as part of training or inference pipelines.

Compensation and additional information

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary ranges provided are:

• Level 4: 184,000 USD - 287,500 USD
• Level 5: 224,000 USD - 356,500 USD

You will also be eligible for equity and benefits. Applications for this job will be accepted at least until July 12, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer. They do not discriminate in hiring and promotion practices on the basis of protected characteristics.