Machine Learning Engineer

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 (Py. Torch, Tensor. Flow, 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.