Robotics Autonomy ML Engineer - VLA & Manipulation

Deft AI, Inc.; San Francisco (CA); On-site; Full time

Job description

What you'll do

• Design and develop a modular robot autonomy stack that composes Vision‑Language‑Action (VLA) models with purpose‑built modules to enable grasping and dexterous behaviors in unstructured environments.
• Develop action refinement and safety layers that post‑process VLA outputs — constraint satisfaction, collision and force guards, smoothing, and runtime monitors for safety‑critical deployment.
• Architect clean interfaces and abstractions around base VLA models so they can be swapped, benchmarked, and upgraded as the SOTA evolves — keeping the stack model‑agnostic.
• Design and maintain robust data collection and curation pipelines for production robot fleets.
• Build reliable, high‑speed robot autonomy software stack optimized for inference performance.
• Advance SOTA dexterous manipulation architecture through novel methodologies while bridging theory & practice—real customer use‑cases with clear success criteria.

Required Qualifications

• PhD or MS degree in Computer Science, Machine Learning, Robotics, or equivalent technical discipline.
• Deep expertise in machine learning fundamentals, reinforcement learning, and associated frameworks (PyTorch, TensorFlow, Ray, etc.).
• 3+ years of proven track record developing and deploying ML systems from research through production implementation.
• Hands‑on experience with model lifecycle management including training, deployment, and maintenance in production settings.

Preferred Qualifications

• Authored or co‑authored peer‑reviewed publications in robotics or related fields.
• Hands‑on experience designing and implementing bimanual manipulation tech stacks with imitation learning or RL‑based methods.
• Background in real‑time ML inference systems, simulation‑to‑reality transfer, or advanced reinforcement learning implementations.

Benefits

• We support publishing at top robotics/ML venues and presenting at conferences (travel + time fully covered).
• Medical, dental & vision plans.
• Daily meals stipend.

Expected Compensation

• $150,000 – $200,000 annual salary + cash and stock awards + benefits.
• The pay offered for this position may vary based on several individual factors, including job‑related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.