Machine Learning Engineer

Rainfall Ventures; San Francisco (CA); On-site; USD 150,000 - 200,000; Full time

Benefits offered by this job

Conference travel covered

Medical, dental & vision plans

Meals stipend

Job summary

Rainfall Ventures in San Francisco seeks a Machine Learning Engineer to design and advance a modular autonomous robot stack that fuses Vision-Language-Action models with purpose-built modules for grasping in unstructured environments.

You will implement action refinement and safety layers, architect interfaces for model swapping, and build robust data pipelines and high-speed inference software for production deployment.

Qualifications

• PhD or MS in Computer Science, Machine Learning, Robotics, or equivalent technical discipline.
• Deep expertise in ML fundamentals and reinforcement learning; familiarity with ML frameworks (PyTorch, TensorFlow, Ray).
• 3+ years of proven track record deploying ML systems from research to production.
• Hands-on experience with model lifecycle management: training, deployment, and maintenance.

Responsibilities

• Design and develop a modular robot autonomy stack that combines Vision-Language-Action models with specialized modules for grasping and dexterous behaviors in unstructured environments.
• Implement action refinement and safety layers to post-process VLA outputs: constraint satisfaction, collision and force guards, smoothing, and runtime monitors for safety-critical deployment.
• Architect clean interfaces around base VLA models to enable swapping, benchmarking, and upgrades as SOTA evolves.
• Design and maintain data collection and curation pipelines for production robot fleets.
• Build high-speed robot autonomy software stack optimized for inference.

Skills

ML fundamentals

Reinforcement learning

Frameworks: PyTorch

Frameworks: TensorFlow

Frameworks: Ray

Education

PhD or MS in CS/ML/Robotics

Tools

PyTorch

TensorFlow

Ray

Job description

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 (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 + 2 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.

Onsite Work Requirement

This is a full-time, five-day-a-week onsite role in our San Francisco, CA, office.

US Work Authorization

Are you a US Citizen, Green Card Holder or Valid Visa Holder (H1-B, O-1, TN, E-3, OPT, etc)?