Senior Software Engineer, Multi-Sensor-Fusion - Autonomous Vehicles

NVIDIA•Us, CA

About The Position

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 software Engineer in multi-sensor fusion for obstacle perception to develop and productize NVIDIA's autonomous driving solutions. As a member of our perception team, you will work on building world class solutions for the obstacle perception by tracking and fusing multiple frames from multiple sources of detections. You will be challenged to improve robustness and accuracy as well as efficiency of the solutions to fully enable autonomous driving anywhere and anytime.

Requirements

PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
Experience in related fields of SW development, with the most recent 5+ years of hands-on work experience in developing perception and fusion algorithms to solve sophisticated real world problems.
Familiar with common data association and fusion algorithms.
Experience in data-driven development and collaboration with data and ground truth teams.
Strong programming skills in modern C++.
Outstanding communication and teamwork skills as we work as a tightly-knit team, always discussing and learning from each other.

Nice To Haves

Proven expertise in developing perception solutions for autonomous driving or robotics.
Hands-on experience in Camera, Radar, Lidar and/or ultrasonic sensors.
Background in multi-view geometry and occupancy grid tracking is a plus, but not required.

Responsibilities

Design and develop a robust tracking and fusion algorithm that improves the accuracy and consistency of the detection of dynamic obstacles, moving or stationary, such as vehicles, VRUs, cones and barrels, and road hazards.
Identify and analyze the strength and weakness of the developed obstacle perception and fusion under complicated and diverse scenarios.
Productize the developed perception solutions by meeting product requirements for safety, latency, and SW robustness.
Define and develop meaningful performance metrics for the perception of dynamic obstacles, which guide the algorithm iterations and prevent regression with large-scale offline data sets.