We are looking for a 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:
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.
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.
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:
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.
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).
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.
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.
This position is open to all candidates.
