Meta Reality Labs Research Team is seeking Research Scientists to research and build egocentric machine perception functionalities for future contextual AI-enabled devices, innovating novel computer vision and machine learning techniques.
Requirements
- 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
- 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)
- 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
Responsibilities
- 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.
- 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.
Other
- 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
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
- Preference for 24 week full time internship
- Intent to return to a degree-program after the completion of the internship
- Experience working and communicating cross functionally in a team environment
