Research Scientist (Reinforcement Learning)

Location: Waltham Office, United States

Salary: $175,000–$230,000 annually, plus an annual bonus structure.

Company

hirify.global develops advanced humanoid robots and commercial robotics solutions for industrial, logistics, and warehouse applications.

What you will do

• Design, implement, and train reinforcement learning algorithms for whole-body mobile manipulation and bimanual manipulation tasks.
• Develop tested, documented, production-ready Python and C++ software.
• Build and use high-fidelity simulation environments such as Isaac Sim and MuJoCo to validate reinforcement learning policies.
• Integrate learned policies with Atlas’s control and software stack in collaboration with controls and platform teams.
• Deploy, debug, and iterate policies directly on physical Atlas hardware.
• Contribute to design reviews, experimental planning, and research direction.

Requirements

• MS or PhD in Computer Science, Machine Learning, Robotics, or a related field.
• Strong experience training and deploying reinforcement learning policies for complex behaviors in robots or simulated agents.
• Proficiency with modern machine learning frameworks, including PyTorch, TensorFlow, or RLlib.
• Strong foundations in algorithms, debugging, performance optimization, kinematics, dynamics, and robotics fundamentals.
• Excellent Python and C++ programming skills with experience contributing to production-scale software.

Nice to have

• PhD or equivalent research experience in reinforcement learning or robotic manipulation.
• Experience deploying reinforcement learning policies on physical robots.
• Experience developing locomotion, bimanual manipulation, or whole-body control behaviors.
• Contributions to large software projects or open-source machine learning and robotics frameworks.
• Publications in top-tier robotics or machine learning conferences such as CoRL, RSS, ICRA, or NeurIPS.

Culture & Benefits

• Direct access to humanoid robots and infrastructure for large-scale reinforcement learning experiments.
• Collaborative, mission-driven work focused on advancing real-world humanoid robotics.
• Medical, dental, and vision benefits.
• 401(k), paid time off, and an annual bonus structure.