Senior Perception Engineer for Autonomous Trucks

Applied Intuition

United States

On-site

USD 150,000 - 230,000

Full time

14 days+

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Job summary

Applied Intuition, Inc. is seeking a Perception Software Engineer on the Autonomy team to build the perception system for L4 autonomous trucks. You will own end-to-end development from model design and training to onboard deployment and on-road validation.

This is safety-critical software with formal simulation, closed-course and safety sign-off gates before public road use. Collaboration with behavior/planning, systems, and validation teams is expected.

Qualifications

  • 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.

Responsibilities

  • 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.

Skills

Python
C++
ML-based perception
Computer vision

Education

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

Tools

PyTorch

Job description

Applied Intuition, Inc. is seeking a Perception Software Engineer on the Autonomy team to build the perception system for L4 autonomous trucks. You will own end-to-end development from model design and training to onboard deployment and on-road validation.

This is safety-critical software with formal simulation, closed-course and safety sign-off gates before public road use. Collaboration with behavior/planning, systems, and validation teams is expected.

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