[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All Meta Platforms jobs](https://jobs.opennash.com/companies/meta-platforms/) · [Search jobs](/search/) Meta Platforms · Menlo Park, CA # Research Scientist Intern, Robotics Foundation Models Mid-Training (PhD) Menlo Park, California, US Internship or early career Early career Research & Science Listed on Meta Platforms’s official careers site. Posted October 14, 2026. Check that it is still open and apply there. [Apply on Meta Platforms’s careers site →](https://www.metacareers.com/jobs/1658187582680157/) [OpenNash Jobs](https://jobs.opennash.com/) / [Meta Platforms](https://jobs.opennash.com/companies/meta-platforms/) / Research Scientist Intern, Robotics Foundation Models Mid-Training (PhD) ## Job description Meta Reality Labs Research is a team of researchers and engineers pushing the frontier of AI and robotics. Our team is building the next generation of world action models (WAMs) and vision-language-action models (VLAs) for robotic manipulation. We are seeking a Research Scientist Intern to develop scalable methods for mid-training world action models on large-scale egocentric video and robot data. Interns in this role will conduct fundamental and applied research to advance foundation models for robotics, with a focus on mid-training. You will collaborate with research scientists and engineers to develop new algorithms, build and evaluate model capabilities, and contribute to the next generation of embodied AI. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year. ## Responsibilities Develop scalable mid-training methods for WAMs using large-scale egocentric video and heterogeneous robot data. Investigate representation and objective design for learning from human egocentric video. Address challenges in training on web-scale, weakly-labeled data, including embodiment and viewpoint gaps, data curation and filtering, and domain mixture weighting. Build efficient training and data pipelines, and study how downstream policy performance scales with dataset size, model capacity, and compute. Design experiments and benchmarks to measure what mid-training contributes, isolating its effect on downstream post-training and generalization across tasks and embodiments. Collaborate with research scientists and engineers to evaluate mid-trained models in simulation and on real robots. Communicate research findings and publish results at leading machine learning, computer vision, and robotics venues. ## Qualifications - Research experience in training of video models or robotics foundation models Experience implementing and training deep learning models using Python and PyTorch or a comparable framework Experience designing controlled experiments, analyzing results, and debugging machine learning algorithms Interpersonal experience: cross-group and cross-culture collaboration - Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment Intent to return to degree program after the completion of the internship/co-op Experience training VLAs, WAMs, or other foundation models for embodied decision-making Experience with diffusion or flow-based policies, action-sequence prediction, or action-conditioned world models Hands-on experience with distributed training across multiple GPUs or nodes, including improving training throughput, memory efficiency, and stability Experience evaluating learned policies on physical robots or robotics simulation benchmarks - Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, and/or accepted papers in top conferences or journals such as NeurIPS, ICML, ICLR, CoRL, RSS, ICRA, CVPR, ICCV, ECCV, ACL, etc ## At a glance - Posted by the employer: Oct 14, 2026 - First seen by OpenNash: Oct 18, 2026 - Last checked: Oct 18, 2026 - Listed for: 4 days - Location: Menlo Park, California, US - Employment type: Internship or early career[Apply on Meta Platforms’s careers site →](https://www.metacareers.com/jobs/1658187582680157/) ## More jobs at Meta Platforms ### [Research Scientist Intern, AI & Compute Foundation - MTIA SW (PhD)](https://jobs.opennash.com/companies/meta-platforms/jobs/75216091ee4392e3fc80/) Menlo Park, California, US ### [Research Scientist, AI Language](https://jobs.opennash.com/companies/meta-platforms/jobs/b94c65a7f6f184f210a6/) Menlo Park, California, US ### [Visiting Scholar — Post Training & Research](https://jobs.opennash.com/companies/meta-platforms/jobs/d86369fef4f8b7f0e25f/) Menlo Park, California, US ### [Application Engineer, Salesforce](https://jobs.opennash.com/companies/meta-platforms/jobs/d9335707c0de5397c5a8/) Menlo Park, California, US ### [Business Operations Manager, Infrastructure Data Centers](https://jobs.opennash.com/companies/meta-platforms/jobs/6be16a9a243e95c21cde/) Menlo Park, California, US ## Similar jobs at other companies ### [Senior Research Scientist, Multimodal Foundation Models and Robotics](https://jobs.opennash.com/companies/nvidia/jobs/8ef97f155fc33ed9a5ce/) NVIDIA · US, CA, Santa Clara ### [Senior Applied Research Scientist, Multimodal Foundation Models – Healthcare](https://jobs.opennash.com/companies/nvidia/jobs/2c3130c56e44a394a5bb/) NVIDIA · US, CA, Santa Clara ### [Staff Research Scientist - Foundation & World Models](https://jobs.opennash.com/companies/datadog/jobs/58ee1e1f6b45371172e4/) Datadog · New York ### [Research Scientist / Engineer, Foundation Model Evaluation](https://jobs.opennash.com/companies/apple/jobs/6cce92c3dcfb005f56da/) Apple · Cupertino, United States of America ### [AI Research Scientist: Multimodal Foundation Models - Architecture, Pre-Training & Distillation](https://jobs.opennash.com/companies/apple/jobs/ddec3d9e4aa9f99c549d/) Apple · Seattle, United States of America OpenNash lists jobs from employers’ own careers sites and does not handle applications. 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