Lead 3D Perception Engineer for Autonomous Driving

NVIDIA Corporation

Santa Clara (CA)

On-site

USD 272,000 - 431,000

Full time

14 days+

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Job summary

NVIDIA seeks a Principal Perception Engineer to lead the design and productization of the next-generation autonomous driving perception stack. You will own the technical direction for 3D obstacle perception, drive cross-functional execution, and mentor engineers while staying hands-on with architecture, algorithms, and implementation.

Role demands 15+ years in deep learning perception, strong leadership, and mastery of PyTorch, Python, and C++.

Qualifications

  • 15+ years hands-on experience in deep learning perception systems.
  • Technical leadership as a senior or principal contributor.
  • Data-driven development with close collaboration to data and labeling teams.
  • Strong Python and C++ production software experience.
  • Excellent communication and cross-functional collaboration skills.
  • BS/MS/PhD in CS, EE, or related field.

Responsibilities

  • Own the technical vision, architecture, and roadmap for 3D obstacle perception.
  • Design and develop advanced 3D perception models with multi-sensor inputs.
  • Lead production-grade deep learning models and experimentation.
  • Define KPI frameworks and improve accuracy, robustness, and efficiency.
  • Lead data strategy, labeling, and model-in-the-loop tooling.
  • Collaborate with safety, systems, and software teams for scalable deployment.
  • Provide technical leadership and mentorship across perception and autonomy teams.

Skills

PyTorch
Python
C++
Deep learning
Leadership
Production deployment
3D perception
Autonomous driving

Education

BS/MS/PhD in Computer Science or Electrical Engineering

Tools

CUDA
TensorRT
ROS2

Job description

NVIDIA seeks a Principal Perception Engineer to lead the design and productization of the next-generation autonomous driving perception stack. You will own the technical direction for 3D obstacle perception, drive cross-functional execution, and mentor engineers while staying hands-on with architecture, algorithms, and implementation.

Role demands 15+ years in deep learning perception, strong leadership, and mastery of PyTorch, Python, and C++.

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