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.
We are now looking for an extraordinary Senior Perception Engineer to develop and productize NVIDIA’s autonomous driving solutions. As a member of our perception team, you will be driving E2E solutions for various components of Wait Condition Perception and Fine grained recognition tasks. You will be challenged to improve robustness and accuracy as well as efficiency of the solutions to fully enable autonomous driving anywhere and anytime.
What you’ll be doing:
Designing end2end 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 SW 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 will include data collection prioritization and planning, labeling prioritization, labeling efficiency optimization, so that value of data is maximized.
What we need to see:
2+ 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 as we work as a tightly-knit team, always discussing and learning from each other.
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. The ability to implement CUDA kernels as part of training or inference pipelines.
You will also be eligible for equity and benefits.
Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
