Nvidia Senior Perception Engineer 

United States, Texas 

502232321

What you’ll be doing:

• Perception experts with application focus will be on obstacle perception/fusion in complex driving environments.

• Applied research and develop innovative deep learning and multiple camera fusion algorithms to improve output accuracy of 3D obstacle perception solutions under challenging and diverse scenarios.

• Identify and analyze the strength and weakness of the developed 3D obstacle perception solutions using large scale benchmark data (both real and synthetic) and improve them iteratively through KPI building and optimization.

• Productize the developed 3D obstacle 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, so that value of data is maximized.

What we need to see:

• 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 leadingconferences/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.