We are looking for an exceptional deep learning algorithm developer with proven experience in LLMs/VLMs/VLA models to join our growing team under our copmpanys Algorithms Group. The team is building an innovative multimodal learning framework aimed at improving autonomous driving performance by understanding long-tail cases and providing actionable navigation insights. Were combining state-of-the-art vision-language models to revolutionize how we train, validate, and scale our autonomous systems. If youre passionate about deep learning and engineering high-impact autonomous solutions - this is the place for you.
What will your job look like:
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).
This position is open to all candidates.