# Machine Learning Engineer - Robot Manipulation

**Company:** [Maven Robotics](https://hotfix.jobs/companies/maven-robotics)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Skills:** Reinforcement Learning, Imitation Learning, PyTorch, Python, Gazebo, Mujoco, Stable Baselines, Rllib, Sim-To-Real Transfer, GPU, Tpu
**Posted:** 2026-02-02

> Designs and deploys reinforcement and imitation learning algorithms for robotic manipulation tasks in dynamic environments. Requires MS/PhD, deep RL/IL expertise, PyTorch proficiency, and real-world ML deployment experience in a fast-paced startup.

## Job Description

## Responsibilities
- Design and implement machine learning algorithms, focusing on **reinforcement learning (RL)** and **imitation learning (IL)**, for robotic manipulators in dynamic environments.
- Translate high-level objectives into ML problems and deploy robust, scalable models to real-world robotic systems.
- Integrate ML solutions into robotics workflows, ensuring performance in simulated and real-world settings.
- Drive innovation by applying latest ML research to robotic manipulation.
- Own critical ML projects from conception to deployment.
- Collaborate across disciplines and mentor junior engineers.

## Requirements
**Must-have:**
- MS or PhD in machine learning, computer science, robotics, or related field.
- Strong experience training and deploying ML models for real-world applications.
- Deep understanding of **RL** and **IL** in robotics.
- Proficiency in **Python**, **PyTorch**.
- Experience with data collection, preprocessing, and management for ML training.
- Self-starter with problem identification, prioritization, and execution skills.
- Enthusiasm for fast-paced startup environment.

**Nice-to-have:**
- Familiarity with **Gazebo**, **MuJoCo**, sim-to-real transfer.
- Designing reward functions for manipulation tasks.
- Models for noisy, incomplete, or sparse data.
- Deployment to edge devices for real-time inference.
- Accelerating training with **GPU**, **TPU**, or accelerators.
- **Stable Baselines**, **RLlib**.
- Robotics principles: kinematics, dynamics, control.
- Publications in ML/robotics/RL.

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