Research Scientist Intern, Policy Learning for Robotics (PhD)

Meta Reality Labs Research is looking for an intern to help us develop the next-generation of policy learning algorithms for robotics applications. In particular, we are seeking candidates who have experience with reinforcement learning, robotic policy learning, diffusion and flow models, vision-language-action models (VLAs), and sim2real to devise effective algorithms to train control policies for dexterous robot manipulation.

Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.

Responsibilities

• Develop and implement strategies for training dexterous robot manipulation policies that are efficient and robust under the complexity of contact.
• Implement and optimize the methods devised on a large-scale cluster infrastructure.
• Collaborate with research scientists and software engineers to build demos and experiences based on the developed tools.
• Plan, write and submit the research to high impact conferences, journals or workshops in the field of robot learning or reinforcement learning for broader visibility.

Minimum qualifications

• Currently is in the process of obtaining a PhD in computer science, machine learning, computational mathematics or a relevant technical field
• Research skills involving defining problems, exploring solutions, and analyzing and presenting results
• Experience implementing numerical methods and/or deep learning models in a large-scale code
• Proficient in Python
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment

Preferred qualifications

• 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 NeurIPS, ICML, ICLR, RLC, IROS, ICRA, RSS, CoRL or similar
• Experience with training deep learning models and familiarity with tools like PyTorch
• Experience with parallel distributed large-scale model training on CPU/GPU clusters
• Experience working and communicating cross functionally in a team environment
• Intent to return to degree program after the completion of the internship/co-op
• Availability for minimum 16 consecutive week internship