Deep Learning Algorithm Developer improving autonomous driving performance at Mobileye. Developing multimodal learning frameworks and collaborating with various engineering teams in a hybrid environment.
Responsibilities
Contribute to dataset curation activities - collecting, cleaning, labeling, and preparing multimodal data for training and validation.
Train and fine-tune LLMs, VLMs, and VLA models to interpret visual scenes and produce actionable navigation insights supporting autonomous vehicle decision-making.
Support validation of multimodal models - evaluating vision-language-action behavior and helping identify performance gaps across driving scenarios.
Collaborate closely with AV planners, perception teams, and infrastructure engineers to ensure seamless deployment in a real-time ecosystem.
You’ll have the opportunity to influence the strategic direction of language-driven autonomy - proposing new ideas, shaping model capabilities, and driving innovation from research to real-world deployment.
Requirements
M.Sc. in Deep Learning, Computer Vision, NLP, or a related field (Ph.D. an advantage).
Hands-on experience in developing deep learning models.
Strong programming skills in Python (additional C++ is an advantage).
Experience with modern DL frameworks (e.g., PyTorch, TensorFlow).
Experience with large multimodal or language models (LLMs/VLMs/VLA models) and their real-world integration - advantage.
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