Senior Machine Learning Engineer, Perception - Autonomous Driving

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +2 · Remote

NVIDIA is seeking a Senior Machine Learning Engineer for their autonomous driving perception team. The role involves designing and developing end-to-end deep learning solutions for perception modules, focusing on road layout detection and other critical driving components. Responsibilities include applied research, data-driven development, and productizing solutions with a focus on safety, latency, and robustness. Experience with deep learning frameworks, Python/C++, and perception for autonomous driving or robotics is required.

What you'd actually do

  1. Designing end2end solutions for Perception and AV stack to enable road network detections across various driving environments from complex intersections to rural curvy roads to multi-level highways.
  2. Applied research and development of innovative deep learning models for lane graph construction, road boundary detection, traffic element recognition, and other static-world tasks.
  3. Develop generalizable approaches to support diverse ODDs and Country/region expansion
  4. 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
  5. Leverage data simulation and augmentation for solving extreme scenarios
  6. Productize the developed perception solutions by meeting product requirements for safety, latency, and SW robustness.

Skills

Required

  • PhD or MS or BS with equivalent experience in Computer Science, Computer Engineering, or related field
  • Deep learning frameworks (e.g., PyTorch)
  • Python
  • C++

Nice to have

  • Technical leadership
  • Transformers
  • BEV architectures
  • Modern static-world perception techniques
  • Deep learning publications
  • Deploying DNN-based solutions to embedded platforms
  • Cameras
  • Robotics

What the JD emphasized

  • PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience
  • Hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems
  • Experience in data-driven development and collaboration with data and ground truth teams.
  • 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.

Other signals

  • develop and productize NVIDIA’s autonomous driving solutions
  • designing end2end solutions for Perception and AV stack
  • Applied research and development of innovative deep learning models
  • Productize the developed perception solutions by meeting product requirements for safety, latency, and SW robustness