We are looking for a senior deep learning algorithm developer to join our growing team under 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:
Own dataset curation activities- acquiring, cleaning, labeling, and tailoring multimodal data to meet model training and validation requirements.
Train and fine-tune LLMs, VLMs, and VLA models to interpret visual scenes and produce actionable navigation insights supporting autonomous vehicle decision-making.
Lead robust validation of advanced multimodal models - ensuring reliable vision-language-action alignment and consistent performance across diverse real-world driving scenarios.
Collaborate closely with AV planners, perception teams, and infrastructure engineers to ensure seamless deployment in a real-time ecosystem.
Youll 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).
At least 5 years of hands-on experience developing deep learning models, including a minimum of 2 years of industry experience in the field.
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.
This position is open to all candidates.