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NVIDIA

Designs the chips and software that power AI

Director Perception - Autonomous Vehicles

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeUnited StatesIn-person

About the Job

Requirements

  • A Ph.D. or master's degree in computer science, Robotics, Artificial Intelligence, visual computing, or a related field, or equivalent experience.
  • At least 10 years of industry experience in deep learning, computer vision, or autonomous robotics, including at least 5 years in a senior leadership role managing large teams or multiple layers of management.
  • Deep theoretical and practical expertise with modern network architectures, including Transformers, convolutional neural networks, and foundation models, and complex multi-sensor fusion paradigms.
  • A track record of deploying production-grade, safety-critical machine learning models to edge or embedded computing platforms.
  • Foundational knowledge of Python, C++, and deep learning frameworks such as PyTorch, JAX, or TensorFlow.
  • Ability to distill complex technical uncertainty into clear, actionable strategies for teams and executive leadership.

Responsibilities

  • Lead, mentor, and scale an organization of engineering managers, applied researchers, and software engineers focused on autonomous vehicle perception.
  • Guide the strategic direction, design, and execution of modern network architectures, including Transformers, BEV, Occupancy Networks, and Vision-Language-Action models, for multi-sensor fusion using cameras, LiDAR, and radar, and real-time 3D world reconstruction.
  • Oversee the machine learning lifecycle, from active learning, data mining, and synthetic data generation through model training, model performance acceleration, and deployment on NVIDIA DRIVE platforms, including Orin and Thor.
  • Partner with leaders in Planning and Control, Mapping, Hardware, and Safety to integrate the perception stack and align on autonomous-vehicle system-level metrics.
  • Ensure algorithms and production code adhere to automotive quality and safety standards, including ISO 26262.

Desired Qualifications

  • Demonstrated success shipping autonomous vehicle software to mass production.
  • A recognized presence in the global artificial intelligence and computer vision community, evidenced by top-tier publications such as CVPR, ICCV, or NeurIPS, or significant open-source contributions.
  • Hands-on experience with next-generation paradigms such as end-to-end autonomous driving architectures, Large Vision Models, or sim-to-real transfer techniques.
  • Deep understanding of hardware-software co-design, specifically optimizing modern networks for NVIDIA GPU architectures.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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