Machine Learning Engineer

Deft AI • San Francisco, CA

13d • Onsite

About The Position

We are seeking a talented Machine Learning Engineer to design and develop a modular robot autonomy stack. This role involves composing Vision-Language-Action (VLA) models with purpose-built modules to enable grasping and dexterous behaviors in unstructured environments. You will develop action refinement and safety layers, architect clean interfaces for VLA models, and design robust data collection pipelines. The goal is to build a reliable, high-speed robot autonomy software stack optimized for inference performance and to advance the state-of-the-art in dexterous manipulation architecture.

Requirements

• 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

Nice To Haves

• 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

Responsibilities

• 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.

Benefits

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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree