Robotics ML Engineer: Manipulation & RL

Maven Robotics, Inc.; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Maven Robotics, Inc. in San Francisco seeks a skilled Machine Learning Engineer - Robot Manipulation to design, implement, test, and deploy manipulation algorithms for assembly and material handling.

You will work across RL and IL, translate goals into robust models, and ensure real‑world performance on robotic systems, while mentoring teammates in a fast‑paced startup. Experience with Gazebo/MuJoCo and edge deployment is a plus.

Qualifications

• MS or PhD in machine learning, computer science, robotics, or a related field.
• Strong practical experience training and deploying machine learning models for real-world applications.
• Deep understanding of reinforcement learning (RL) and imitation learning (IL) and their application to robotics.

Responsibilities

• Design and implement machine learning algorithms, with a focus on RL and IL, to enable robotic manipulators to perform complex tasks in dynamic environments.
• Translate high-level objectives into machine learning problems and deploy robust, scalable models to real-world robotic systems.
• Integrate ML solutions into existing robotics workflows, ensuring models perform well in simulated and real-world settings.
• Drive innovation by incorporating latest research in ML into practical applications for robotic manipulation.
• Take ownership of critical ML projects from conception to deployment.
• Collaborate across disciplines and mentor junior engineers.

Skills

Python

PyTorch

Reinforcement Learning

Imitation Learning

Data management

Self-starter

Startup environment

Education

MS in ML/CS/Robotics

PhD in related field

Tools

Gazebo

MuJoCo

Stable Baselines

RLlib

Job description

Maven Robotics, Inc. in San Francisco seeks a skilled Machine Learning Engineer - Robot Manipulation to design, implement, test, and deploy manipulation algorithms for assembly and material handling.

You will work across RL and IL, translate goals into robust models, and ensure real‑world performance on robotic systems, while mentoring teammates in a fast‑paced startup. Experience with Gazebo/MuJoCo and edge deployment is a plus.