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AI Engineer, LIGHT

Responsibilities

  • Design end-to-end differentiable systems that jointly optimize sensor control, illumination patterns, and perception tasks (detection, segmentation)
  • Develop domain adaptation techniques enabling synthetic-to-real transfer without retraining.
  • Implement energy-aware AI models balancing perception quality with power constraints for embedded automotive deployment.
  • Validate systems through real-world vehicle testing across diverse environmental conditions.
  • Publish research at top-tier conferences (CVPR, ICCV, NeurIPS) while delivering production-ready solutions.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or a related field.
  • 3+ years developing and deploying deep learning and reinforcement learning models
  • Expert-level deep learning (PyTorch/TensorFlow) with custom architecture design.
  • Strong background in object detection, semantic segmentation, neural rendering.
  • Experience with domain adaptation, self-supervised learning, and model optimization for
  • edge devices.
  • Familiarity with ROS, simulation environments (CARLA, Applied Intuition, NVIDIA), and 3D
  • rendering engines.
  • Experience with automotive perception datasets (nuScenes, Waymo Open, KITTI) and
  • benchmarks.
  • Hands-on experience with automotive sensors (cameras, LiDAR, radar, thermal imaging).
  • Knowledge of closed-loop control integration with neural networks.
  • Proficiency in Python, C++, and CUDA programming.

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