About this role

Design and train Vision-Language-Action (VLA) solutions for robotaxis
Lead end-to-end data strategy, including mining, auto-labeling, and dataset construction to power our ML flywheel
Lead the full post-training stack for VLMs and VLAs, including Continual Pre-training (CPT) on domain-specific driving data, Supervised Fine-Tuning (SFT) for instruction following.
Utilize large-scale data pipelines and ML infrastructure to research, prototype, and deploy solutions that improve driving behavior
Partner with cross-functional teams to integrate perception signals

MS or PhD in Computer Science or related field
Background in deep learning solutions for VLM and VLA models
Track record in post-training large-scale models, CPT, SFT, RL
Hands-on experience with production ML pipelines, including dataset creation, training frameworks, and metrics
Expertise in Python libraries (PyTorch, NumPy, Pandas, VLLM)

Senior Machine Learning Engineer – Scene Understanding

Key skills