Autonomy Engineer - VLA Pre-training

Responsibilities

• Pre-train and post-train vision-language-action policies using behavior cloning and reinforcement learning.
• Own the full model development loop from data collection and curation through deployment.
• Define high-quality data requirements, identify failure modes, and ensure dataset diversity and coverage.
• Coordinate with external partners to maintain a reliable supply of pretraining-scale data.
• Run pre-training, mid-training, and post-training on the VLA stack while exploring new modalities and architectures.
• Build continuous pipelines for synthetic data and teleoperation logs, including versioning, weak-supervision labeling, balanced dataset curation, and automated failure-case discovery.
• Partner with MLOps and Data Platform teams to scale distributed training and optimize models for real-time edge inference.

Requirements

• At least 3 years of experience building deep-learning systems in industry or research, with shipped models or published artifacts.
• Hands-on experience with at least one of LLMs, VLMs, or image/video generative models, including architecture, training, and inference.
• Experience with streaming datasets, checkpointing, state management, and distributed training strategies.
• Strong Python and PyTorch or JAX skills, including profiling, numerical debugging, and maintainable research-code development.
• Familiarity with modern software engineering practices and the ability to document experiments and communicate trade-offs clearly.
• Robotics or autonomous-driving experience is preferred.
• Experience applying reinforcement learning to LLMs or robotics is preferred.
• Experience with VLA models, deep-net productization, latency and throughput constraints, telemetry, or on-device optimization is preferred.
• Publications at top-tier deep-learning conferences or equivalent open-source contributions are preferred.
• Familiarity with OpenVLA, Physical Intelligence models, or similar open-source VLA frameworks is preferred.

Benefits

• Comprehensive health coverage for US-based employees, including fully paid medical, dental, and vision insurance, virtual care, and employee assistance resources.
• 23 accrued PTO days, separate sick leave, and paid company holidays.
• 401(k) retirement plan with employer match.
• Equity participation.
• Free daily catered lunch, snacks, and drinks in the office.
• Opportunity to collaborate with engineers, researchers, and product experts in AI and robotics.
• Freedom to influence the product and own key initiatives.
• California role with an expected base salary range of $180,000–$300,000 USD per year.