Principal Perception Engineer

Details

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. Now, NVIDIA’s GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world.

Responsibilities

• Designing end-to-end solutions for Perception and AV stack to enable wait condition and fine grained classification tasks in complex driving environments. Example perception signals include traffic light, traffic signs, roadmarks, texts, classes of dynamic objects, and vehicles’ light signals (brake, turn, hazard etc).
• Applied research and development of innovative deep learning models. Additionally, develop localization and tracking algorithms to improve output accuracy of detection and classification solutions under challenging and diverse scenarios.
• Develop generalizable approaches to support ODD and Country/region expansion.
• Productize the developed perception solutions by meeting product requirements for safety, latency, and software robustness.
• 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 include data collection prioritization and planning, labeling prioritization, and labeling efficiency optimization to maximize the value of data.

Requirements

• 4+ years of technical leadership demonstrating high technical and organizational complexity.
• 12+ years of hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems, and proficiency in using deep learning frameworks (e.g., PyTorch).
• Experience in data-driven development and collaboration with data and ground truth teams.
• Strong programming skills in Python and/or C++.
• Outstanding communication and teamwork skills.
• BS/MS/PhD in CS, EE, sciences or related fields (or equivalent experience).

Ways to Stand Out from the Crowd

• Proven expertise in developing 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.
• Good understanding of fundamentals of 3D computer vision, camera calibrations including intrinsic and extrinsic.
• Experience with development in CUDA language, including the ability to implement CUDA kernels as part of training or inference pipelines.

Benefits

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. They do not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.