aimlroles

Senior Machine Learning Engineer, Perception - Autonomous Driving

NVIDIA nvidia.com Open · verified Oct 22, 2026
US, CA, Santa Clara Full-time Senior Machine Learning Engineering

At a glance

Senior Machine Learning Engineering role at NVIDIA. US, CA, Santa Clara · full-time.

In listing Machine Learning Engineer salary

RoleMachine Learning Engineering
SenioritySenior
LocationUS, CA, Santa Clara
EmploymentFull-time
PostedOct 6, 2026 · 2w ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build and tune machine learning models for LiDAR and camera perception, including detection, classification, segmentation and tracking
  • Coordinate the full ML workflow, from data pipelines and training through metrics, ongoing performance checks and reporting
  • Move models from experiments into the DRIVE AV product, writing efficient C++ code
  • Track advances in machine learning and work with perception teams and engineers to turn useful ideas into autonomous-driving systems

What you bring

  • A master's or doctorate in computer science, engineering or a related discipline, or equivalent experience
  • At least eight years applying machine learning to practical problems in industry
  • Strong C++ and Python skills, including debugging complex software systems
  • Hands-on work with LiDAR or camera perception and sensor fusion in automotive or a related field

Who this fits

This senior individual-contributor role suits an experienced ML engineer focused on perception for autonomous driving. You should be comfortable developing models and workflows as well as bringing efficient C++ implementations into a product.

From the employer

Intelligent machines powered by Artificial Intelligence computers that can learn, reason, and interact with people are no longer science fiction. Today, a self-driving vehicle powered by AI can meander through a country road at night and find its way. NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots, and self-driving vehicles that can perceive and understand the world.


Our team is building the machine learning backbone of the Perception component for NVIDIA DRIVE AV. We are seeking the best Machine Learning Engineers with a background in computer vision, LiDAR & camera perception, multi-sensor fusion and AI infrastructure who are passionate about solving the hardest problems for self-driving cars. Are you interested in inventing human-level AI for perception under real world conditions? If so, join us!


What You'll Be Doing:

  • Model Development: Design, train, and optimize innovative machine learning models for LiDAR/camera perception and multi-sensor fusion (e.g., object detection/classification, image classification, semantic segmentation, tracking).
  • Develop and coordinate entire ML workflows, covering data pipelines, model training, model metrics, continuous performance instrumentation, and reporting.
  • Productization: Take ML models and algorithms from initial evaluation and experimentation all the way to product level on the NVIDIA DRIVE AV platform, developing highly efficient product code in C++.
  • Innovation: Keep track of the latest developments in machine learning, and incorporate techniques that improve platform performance.
  • Collaborate with LiDAR/camera teams, developers, engineers, and managers to turn complex ideas into reliable solutions for autonomous driving.

What We Need to See:

  • MS or PhD in Computer Science, Engineering, or a related field, or equivalent experience.
  • 8+ years of relevant proven industry experience applying machine learning to address real-world problems.
  • Strong C++ and Python programming and debugging skills with experience in developing for large, complex systems.
  • Deep practical experience applying machine learning to lidar/camera perception and multi-sensor fusion in automotive or related fields.
  • Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and a strong understanding of the mathematical foundations of ML.
  • Building and sustaining training and essential metric workflows for large-scale datasets.
  • Excellent communication and analytical skills. Self-motivated drive to solve hard problems.

Ways to Stand Out From the Crowd:

  • Multi-sensor fusion, LiDAR or Camera Perception Experience: Proven track record of developing and shipping deep learning models for LiDAR/Camera and Multi-Sensor Fusion in a production environment.
  • Advanced Model Knowledge: Familiarity with modern network architectures like Transformers and their application to visual recognition tasks.
  • AV Production Experience: A history of delivering ML features and models into a production autonomous vehicle stack or a related robotics product.
  • Performance Optimization: Experience with model optimization for real-time inference on embedded or automotive platforms (e.g., using TensorRT).

We believe that realizing self-driving vehicles will be a defining contribution of our generation (e.g., traffic accidents are responsible for ~1.25 million deaths per year worldwide). We have the funding and scale, but we need your help on our team. NVIDIA is widely considered to be one of the technology world’s most desirable employers with some of the most brilliant and talented people in the world working here. If you're creative and autonomous, we want to hear from you!


#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 October 10, 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.