Join Applied Intuition as a Perception Software Engineer to develop safety-critical perception systems for L4 autonomous trucks.
Posted by employer 3 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 16 hours ago
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Not disclosed in this posting: compensation, visa sponsorship.
Benefits
Joblaze summary
In the role of Perception Software Engineer at Applied Intuition, the individual will focus on developing and deploying perception systems for Level 4 autonomous trucks, ensuring safety and reliability through rigorous testing. Key skills include expertise in machine learning, particularly in 3D object detection and sensor fusion, with proficiency in Python and C++. This position is ideal for seasoned professionals with a background in robotics or computer vision, particularly those experienced in safety-critical software development. The team operates in a fast-paced environment, collaborating closely with engineers across various disciplines to advance autonomous technology.
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From the original posting
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.
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
Bachelor's degree in Computer Science, Robotics, Electrical Engineering, or a related field
4+ 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
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
Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.
Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.
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