Senior Perception Engineer - Autonomous Vehicles

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Senior Perception Engineer at NVIDIA focused on developing and productizing autonomous driving solutions using deep learning and multi-sensor fusion. The role involves applied research, algorithm development, model robustness/accuracy improvement, and productionizing perception solutions for safety and latency.

What you'd actually do

  1. Perception experts with application focus will be on multi-sensor fusion based deep learning model development for obstacle perception/fusion in complex driving environments.
  2. Applied research and development of innovative deep learning and multi-sensor fusion algorithms to improve output accuracy of 3D obstacle perception solutions under challenging and diverse scenarios.
  3. Identify and analyze the strength and weakness of the developed 3D obstacle perception solutions using large scale benchmark data (both real and synthetic) and improve them iteratively through KPI building and optimization. This includes careful data verification, model architecture design, understanding details of loss function engineering, and being capable of finding detailed ML bugs and iterating toward perfection.
  4. Productize the developed 3D obstacle perception solutions by meeting product requirements for safety, latency, and SW robustness, with a strong emphasis on production deep learning model development.
  5. 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, so that value of data is maximized.

Skills

Required

  • 5+ years of hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems
  • proficiency in using deep learning frameworks (e.g., PyTorch)
  • Experience in multi-sensor fusion (cameras, ultrasonic sensors, radar) for perception tasks, particularly in high-resolution world reconstruction
  • Proven experience in production deep learning model development, including careful 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++

Nice to have

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

What the JD emphasized

  • production deep learning model development
  • deep learning
  • multi-sensor fusion

Other signals

  • deep learning
  • autonomous driving
  • multi-sensor fusion
  • production deep learning model development