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The research intern will work on cutting edge research problems to innovate novel computer vision and machine learning techniques. Work with researchers to advance frontier generative AI in the following areas: -Develop unified predictive models that integrate language, vision, human motion, and actions. -Investigate techniques to enable long-horizon, consistent and physically grounded generation. -Benchmark against state-of-the-art approaches in world modeling, video generation, and vision–language–action model. -Leverage multimodal generation to accelerate robot learning and control. Build contextual and embodied AI models using large-scale egocentric multimodal datasets.
Job Responsibility:
Plan and execute cutting-edge research and development to advance the state-of-the-art in machine learning and large-scale training
Collaborate with other researchers and engineers across machine perception teams at Meta to develop experiments, prototypes, and concepts that advance the state-of-the-art contextual AI and robotic systems
Work with the team to help design, setup, and run practical experiments and prototype systems related to large-scale high-quality sensing and machine reasoning
Requirements:
Currently has, or is in the process of obtaining a PhD degree in the domain of computer-vision, computer graphics, 3D machine perception or deep learning
Knowledge in deep learning, computer vision, graphics, generative modeling, LLMs and VLMs
Hands-on experience with implementing deep learning algorithms, large-scale training, benchmark and evaluation
Experience working within Python environments such as pytorch
Experience working in a Unix environment
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Nice to have:
Preference for 24 week full time internship
Intent to return to a degree-program after the completion of the internship
Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at top tier conferences such as CVPR, ECCV, ICCV, SIGGRAPH, ICLR and NeurIPS
Strong track-record of published research in the fields of LLMs, VLMs, video generation, world modeling, VLA, human motion modeling, policy learning, generative modeling etc
Strong programming experience using python and pytorch
Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
Experience working and communicating cross functionally in a team environment