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.
  
  

• 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.