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# Software Engineer - Perception (Fallback Stack

- **Company:** Applied Intuition
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Computer Vision, C++ (Programming Language), Information Engineering, Data Mining, Python (Programming Language), Machine Learning, Object Detection, Sensor Fusion, Pytorch, Deep Learning, Information Technology, Automotive Software, Lidar
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/software-engineer-perception-fallback-stack-appliedintuition-com-8295050

## About the Role

* Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, or a related field
 * 5+ years of professional experience in ML-based perception, computer vision, or robotics
 * Strong proficiency in Python and C++
 * Hands-on experience training and deploying deep learning models in production (e.g., PyTorch)
 * Solid grounding in classical perception: multi-object tracking, state estimation, and 3D geometry

Nice to have:

 * Experience working in modern ML-based perception for autonomous systems
 * Experience with multi-sensor calibration and fusion
 * Experience optimizing models for onboard/embedded GPU inference
 * Background in safety-critical or automotive software development
 * Experience in a startup or fast-paced environment

## Description

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


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