Machine Learning Engineer developing advanced SLAM systems for autonomous trucking environments at Bot Auto. Collaborating with cross - functional teams to optimize mapping solutions and ensure operational stability.
MO
Hybrid Machine Learning Tech Lead Engineer, Multimodal Models – LLM/VLM
Posted 2 months ago
About the role
- Deep learning algorithm developer joining Mobileye's Algorithms Group, focusing on multimodal learning for autonomous driving. Innovating on vision-language models for training and validation of autonomous systems.
Responsibilities
- Lead dataset curation strategy - designing scalable pipelines for multimodal data to drive high-quality training and validation.
- Architect and optimize LLMs, VLMs, and VLA models - transforming scene understanding into reliable driving guidance.
- Own the validation strategy - defining methodologies, metrics, and failure-analysis workflows for robust vision-language-action alignment.
- Make an immediate impact by applying deep expertise to guide model design, methodology, and development priorities from day one.
- Collaborate closely with AV planners, perception teams, and infrastructure engineers to ensure seamless deployment in a real-time ecosystem.
- Influence the technical direction of language-driven autonomy - contributing experience, shaping capabilities, and driving innovation to production.
Requirements
- M.Sc. in Deep Learning, Computer Vision, NLP, or a related field (Ph.D. an advantage).
- Proven experience with large multimodal or language models (LLMs/VLMs/VLA models) and their real-world integration.
- At least 7 years of 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).
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