Machine Learning Engineer (Reinforcement Learning)

Location: Pittsburgh or San Mateo, United States

Base salary: $100,000–$300,000 USD per year

Company

Develops general-purpose robotic intelligence using data-driven machine learning to help robots adapt to unseen scenarios and perform complex tasks autonomously.

What you will do

• Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
• Design and conduct experiments to train reinforcement learning models and evaluate them in real-world robotic environments.
• Collaborate with researchers on novel methods for scaling reinforcement learning model training.
• Work with inference, application, and deployment engineers to integrate reinforcement learning models into robotic systems.
• Analyze experimental results and iterate on model designs to improve performance and deployment robustness.
• Track current research and advancements in reinforcement learning.

Requirements

• Bachelor’s, master’s, or doctoral degree in computer science, robotics, engineering, or a related field, or equivalent practical experience.
• Proficiency in Python, C++, or a similar programming language.
• Experience with at least one deep learning library, such as PyTorch, TensorFlow, or JAX.
• Deep practical understanding of reinforcement learning algorithms and techniques, including model-free, model-based, multi-task, hierarchical, or multi-agent approaches.
• Strong background in algorithms, data structures, and software engineering principles.
• Experience with physics simulation engines and tools for reinforcement learning training, plus industry experience with reinforcement learning and robotic systems.

Culture & Benefits

• Work on general-purpose robotic intelligence designed to adapt to previously unseen scenarios.
• Collaborate across robotics, research, inference, application, and deployment engineering.
• Contribute to projects focused on large-scale, data-driven machine learning for real-world robot deployment.