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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.
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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.
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