Senior Machine Learning Engineer, Perception - Autonomous Driving

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.

• 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.

• 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, Tensor Flow) 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.

• 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!

#Autonomous Vehicles

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.

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