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 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

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