Machine Learning Engineer

Deft AI

  • San Francisco, California
  • 30+ days ago

    Highlights

    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. 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.

    Numbers & Facts

    LocationSan Francisco, California
    Websitehttps://www.deftai.co/

    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


    Hiring Process
    Phone screen + 3 virtual technical interviews + onsite


    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.

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