Senior 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. 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 Autonomous Vehicle (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. Developing localization and tracking algorithms to improve output accuracy of detection and classification solutions under challenging and diverse scenarios.
• Developing generalizable approaches to support Operational Design Domain (ODD) and country/region expansion.
• Productizing the developed perception solutions to meet product requirements for safety, latency, and software robustness.
• Driving and prioritizing data-driven development by collaborating with large data collection and labeling teams to enhance perception system accuracy, including data collection prioritization, labeling prioritization, and labeling efficiency optimization.

Requirements

• At least 2 years of technical leadership demonstrating high technical and organizational complexity.
• 12+ years of hands-on experience developing deep learning and algorithms to solve sophisticated real-world problems, with proficiency in deep learning frameworks such as PyTorch.
• Experience in data-driven development and collaboration with data and ground truth teams.
• Strong programming skills in Python and/or C++.
• Excellent communication and teamwork skills.
• BS/MS/PhD in Computer Science, Electrical Engineering, sciences or related fields, or equivalent experience.

Ways to Stand Out

• Proven expertise in developing perception solutions for autonomous driving or robotics using deep learning with cameras.
• Hands-on experience in developing and deploying deep neural network-based solutions to embedded platforms for real-time applications.
• Technical publications in leading conferences or journals in deep learning.
• Good understanding of fundamentals of 3D computer vision, camera calibrations including intrinsic and extrinsic.
• Experience with CUDA language development, including implementing CUDA kernels as part of training or inference pipelines.

Benefits

• Base salary range: $224,000 - $356,500 USD per year, determined based on location, experience, and comparable employee pay.
• Eligibility for equity and additional benefits.
• Inclusive and diverse workplace committed to equal opportunity.