Senior Machine Learning Engineer, Perception - Autonomous Driving

NVIDIA; California (MO); On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Senior Perception Engineer to advance perception modules within autonomous driving solutions, focusing on traffic signal understanding across diverse environments.

You will lead end-to-end development, from model design to data-driven optimization, ensuring robust, low-latency solutions suitable for real-world deployment.

Qualifications

• PhD with 4+ years, MS with 6+ years, or BS with 8+ years in CS/CE or related field.
• 2+ years of technical leadership experience.
• Hands-on experience in developing deep learning algorithms and using DL frameworks (e.g., PyTorch).
• Strong programming skills in Python and/or C++.
• Excellent communication and teamwork in a tightly-knit team.

Responsibilities

• Design end-to-end perception solutions for traffic signal detection across diverse driving environments.
• Develop DL models for traffic light detection, traffic sign recognition, road markings, and related signals.
• Collaborate with data collection and labeling teams to drive data-driven improvements.
• Productize perception solutions meeting safety, latency, and robustness requirements.
• Advance data simulation/augmentation for extreme scenarios.

Skills

Python

C++

Deep learning

PyTorch

Leadership

Education

PhD

MS

BS

Tools

PyTorch

Job description

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. Now, NVIDIA’s GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world.

We are now looking for an extraordinary Senior Perception Engineer to develop and productize NVIDIA’s autonomous driving solutions. As a member of our perception team, you will be driving E2E solutions for perception modules that are responsible for traffic signal understanding — including traffic lights, traffic signs, road markings, construction objects, and other traffic signals critical for driving without reliance on HD maps. You will be challenged to improve robustness and accuracy as well as efficiency of the solutions to fully enable autonomous driving anywhere and anytime.

What You’ll Be Doing

• Designing end2end solutions for Perception and AV stack to enable traffic signal detections across various driving environments from complex intersections to rural roads to highways.
• Applied research and development of innovative deep learning models for traffic light detection, traffic sign recognition, road marking detection, construction object detection, text recognition, and other traffic signal tasks.
• Develop generalizable approaches to support diverse ODDs and Country/region expansion
• Drive and prioritize data-driven development by working with large data collection and labeling teams to bring in high value data to improve perception system accuracy. Efforts will include data collection prioritization and planning, labeling prioritization, labeling efficiency optimization, so that value of data is maximized
• Leverage data simulation and augmentation for solving extreme scenarios
• Productize the developed perception solutions by meeting product requirements for safety, latency, and SW robustness.

What We Need To See

• Minimum Requirement: PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
• 2+ years of technical leadership demonstrating high technical and organizational complexity is a big plus.
• Hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems, and proficiency in using deep learning frameworks (e.g., PyTorch).
• 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 as we work as a tightly-knit team, always discussing and learning from each other.

Ways To Stand Out From The Crowd

• Proven expertise in developing generalizable perception solutions for autonomous driving or robotics using deep learning with cameras.
• Hands-on experience in developing and deploying DNN-based solutions to embedded platforms for real time applications.
• Proven expertise in deep learning backed up by technical publications in leading conferences/journals.
• Expertise with Visual Language Models, Transformers, BEV architectures, and modern traffic signal perception techniques. Experience in working on complex object detection and recognition problems is a big plus.

Intelligent machines powered by AI are no longer science fiction. GPU Deep Learning has made it possible for self-driving cars to learn, perceive, and reason about the world. NVIDIA GPUs power the algorithms that enable both traffic element understanding and scalable perception across global road systems. Join us and help define the future of reliable, data-driven autonomous driving.

AutonomousVehicles

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 25, 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 proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.