Principal Deep Learning Engineer – Perception, Autonomous Driving

at Nvidia
USD 272,000-431,200 per year
SENIOR
✅ On-site

Used Tools & Technologies

Not specified

Required Skills & Competences

Python @ 7 Machine Learning @ 4 Leadership @ 6 Planning @ 6 Technical Leadership @ 6 PyTorch @ 7 Deep Learning @ 4 AI @ 4 Computer Vision @ 4 Robotics @ 4 TensorRT @ 4

Details

NVIDIA is pioneering the future of autonomous driving through its NVIDIA DRIVE platform used by automakers, truck makers, tier-1 suppliers, and robotaxi companies worldwide. This role is for a Principal Deep Learning Engineer on the Autonomous Driving Perception team, leading the development and productionization of state-of-the-art perception systems for vehicles.

Responsibilities

  • Architect and innovate modern deep learning architectures (e.g., Transformers and variants, few-shot learning) for 3D obstacle detection, dense occupancy prediction, semantic segmentation, and multi-object tracking.
  • Develop, train, and deploy production-grade deep learning models to global automotive customers, ensuring safety and high quality.
  • Drive end-to-end productization of perception models with ownership of shipping robust features to customers.
  • Lead corner-case driven development: identify, mine, and solve long-tail corner cases in urban and highway driving.
  • Define data strategy and technical authority on data quality: establish labeling guidelines, quality-control metrics, and work with data operations to ensure high-fidelity ground truth.
  • Provide technical leadership and mentorship for senior engineers; influence cross-functional teams (planning, mapping, infrastructure) and set the technical roadmap for next-generation perception architectures.

Requirements

  • Ph.D. or MS in Computer Science, Robotics, Machine Learning, Computer Vision, or a related field (or equivalent experience).
  • 12+ years of applied research and software engineering experience, with heavy emphasis on deep learning for computer vision.
  • Proven track record as a lead technical contributor shipping commercial, high-quality deep learning software products.
  • Deep foundational knowledge and hands-on experience building architectures for object detection, occupancy networks, semantic/instance segmentation, and temporal tracking.
  • Strong data intuition and experience managing massive datasets, defining labeling taxonomies, and building automated pipelines to surface hard examples and edge cases.
  • Strong programming skills in Python and C++, and experience with deep learning frameworks such as PyTorch.

Ways to stand out

  • Prior experience in autonomous driving or robotics shipping models deployed on edge compute.
  • Experience with model optimization, quantization, and deployment on embedded platforms, especially using NVIDIA TensorRT.
  • First-author publications at top-tier CV/ML conferences (CVPR, ICCV, ECCV, NeurIPS).
  • Experience designing multi-modal perception systems (camera, lidar, radar fusion).

Compensation & other details

  • Base salary range: 272,000 USD - 431,250 USD (final base salary determined by location, experience, and comparable pay).
  • Eligible for equity and company benefits.
  • Applications accepted at least until March 22, 2026.
  • NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer committed to diversity.