Physical-AI Applied Researcher at Mobileye's CTO Group developing algorithms for decision-making in autonomous driving systems. Engaging in high-impact applied research with a focus on safety-critical systems.
Responsibilities
Design and develop novel learning-based algorithms for decision-making and planning in complex physical environments.
Advance model architectures for long-horizon reasoning, multi-agent interaction, and uncertainty-aware prediction.
Integrate deep learning components into structured planning pipelines with clear formal objectives and safety constraints.
Formulate problems mathematically and derive principled learning objectives grounded in real-world system requirements.
Lead research directions from conception to full-scale production.
Develop using Python (PyTorch or similar frameworks) as well as C++/GPU/Cuda.
Requirements
M.Sc/Ph.D. in Computer Science, Electrical Engineering, Robotics, Machine Learning, Applied Mathematics, or a related field.
Proven experience in machine learning and deep learning.
Demonstrated ability to conduct independent research (publications in top-tier venues such as NeurIPS, ICML, ICLR, CVPR, CoRL, etc. - advantage).
Strong programming skills in Python; solid C++ experience - advantage.
Experience in training large-scale models and working with real-world data.
Intellectual curiosity, scientific ownership, and comfort operating in open-ended research environments.
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