Software Engineer - Perception (Fallback Stack)

About the role

Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co http://applied.co.

We are an in-office company, and our expectation is that full-time employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. This in-office expectation does not apply to contractor positions

ABOUT THE ROLE

As a Perception Software Engineer on the Autonomy team, you will build the perception system for L4 autonomous trucks operating at highway speeds. The stack combines state-of-the-art machine learning - multi-modal 3D detection, BEV representations, learned tracking - with rigorous classical perception: state estimation, multi-object tracking, and sensor fusion. You will own problems end-to-end, from model architecture and training through onboard deployment and on-road validation. This is safety-critical software: every capability passes formal simulation, closed-course, and safety sign-off gates before it reaches public roads.

You will collaborate daily with behavior/planning engineers, systems and safety engineers, and validation teams.

AT APPLIED INTUITION, YOU WILL:

- Design, train, and deploy deep learning models for 3D object detection across LiDAR, camera, and radar sensors

- Build multi-sensor fusion architectures that combine independent detection and classification streams

- Characterize perception failure modes, build targeted evaluation sets, and hill-climb system-level metrics

- Build and operate the data engine: shadow-mode comparison against production, automated data mining, and retraining loops

- Contribute to camera- and LiDAR-based localization perception under degraded conditions

- Take your work through the full safety validation pipeline before it operates on public roads

WE'RE LOOKING FOR SOMEONE WHO HAS:

- Bachelor's degree in Computer Science, Robotics, Electrical Engineering, or a related field