Research Scientist Intern, Robotic Control Policy (PhD)

Meta; Redmond (WA); On-site; USD 55,000 - 83,000; Full time

Job summary

Reality Labs Research in Redmond, WA seeks a Research Scientist Intern at the intersection of robotic control, ML, and human-robot interaction. You will develop data-driven ML-powered control policies for dexterous manipulation and teleoperation across robotics platforms.

Internships range 12–24 weeks with multiple start dates. You will collaborate with world‑leading researchers, publish results, and contribute to state-of-the-art frameworks such as RL, imitation learning, and large behavioral

Qualifications

• Currently pursuing or holding a PhD in Computer Science, AI, Robotics, or a related field.
• Strong understanding of robotic manipulation control policies and advancing the field.
• Experience with ROS, Python, PyTorch or JAX, and related languages.
• Proven ability to work in cross-functional teams and communicate research plans and results.

Responsibilities

• Collaborate on developing control policies for robotics platforms.
• Implement ML frameworks for training policies (LBM, Imitation Learning, RL).
• Develop data collection pipelines for dexterous manipulation and benchmark algorithms.
• Coordinate with researchers and partners to communicate progress and results.

Skills

PhD candidate

Robotics control

Python

PyTorch

JAX

ROS

Cross-functional teamwork

Communication

Reinforcement learning

Education

PhD in CS

Tools

ROS

Python

PyTorch

JAX

Job description

At Reality Labs Research, our goal is to explore, innovate and design novel interfaces and hardware for the next generation of virtual, augmented, and mixed reality experiences. We are driving research towards a vision of natural, seamless experiences in XR environments that are effective, enjoyable, and functionally indistinguishable from those in the real world.

As a Research Scientist Intern, you will work at the intersection of robotic control, machine learning, and human-robot interaction, and you will have the opportunity to work with world-leading collaborators and mentors in these fields. Your primary focus will be on developing data-driven/ML-powered robotic control policies for dextrous manipulation and teleoperation applications.

Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year. Some projects may require a minimum of 16 consecutive weeks.

Responsibilities

• Conduct collaborative research on developing control policies for a range of robotics platforms.
• Implement frameworks to train state-of-the-art machine learning control policies such as Large Behavioral Models, Imitation Learning, and Reinforcement Learning.
• Develop robotic data collection pipelines for robotic dextrous manipulation, train models, and benchmark different algorithms.
• Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.

Qualifications

• Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Robotics, or relevant technical field
• Understand state of the art in robotic manipulation control policies, and advancing the technological frontier in an impactful and efficient way
• Experience with RoS, Python, PyTorch or JAX, or other related languages
• Experience working and communicating cross functionally in a team environment
• Interpersonal skills: cross-group and cross-culture collaboration
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as Robotics (RSS, ICRA, IROS, CoRL, T-RO, IJRR), Machine Learning (NeurIPS, ICML, ICLR, AAAI, JMLR), and Computer Vision (CVPR, ICCV, ECCV, TPAMI), or similar
• Experience with modern control policies like reinforcement learning, imitation learning, and large behavioral models
• Familiarity with modeling and analysis used in robotics including kinematics, dynamics, motion planning, perception, task planning, and control theory
• Experience working with robot manipulation
• Experience working and communicating cross functionally in a team environment
• Intent to return to the degree program after the completion of the internship/co-op
• Availability for minimum 16 consecutive week internship