Research Scientist, Computer Vision (PhD)

Meta is seeking Research Scientists to join its Fundamental AI Research (FAIR) organization to work on making significant advances in AI.

We are seeking talented researchers with experience in vision-language models and general AI to join the team to investigate how to build contextually aware AI that will be the foundation for a new paradigm in how we interact and use computers.

The chosen candidate will work with a highly interdisciplinary team of scientists, engineers, and cross-functional partners with a broad range of experiences, perspectives, approaches, and backgrounds, and access cutting-edge technology, resources, and research facilities.

Responsibilities:

Research Scientist, Computer Vision (PhD) Responsibilities:

Develop algorithms based on state-of-the-art machine learning and neural network methodologies.

Define, build and benchmark new capabilities needed for the next generation of AI.

Work with and create large datasets.

Conduct research to advance the science and technology of intelligent machines.

Conduct research towards long-term ambitious research goals while identifying intermediate milestones.

Conduct research that enables learning the semantics of data across multiple modalities (images, video, text, audio, speech and other modalities).

Qualification and experience:

Minimum Qualifications:

Research Experience in deep learning, computer vision, robotics, or AI infrastructure.

Experience with Python and PyTorch.

Experience writing software and executing complex experiments.

Experience communicating research for public audiences of peers.

Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred:

Preferred Qualifications:

Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences such as CVPR, ICCV, ICCV, NeurIPS, SIGGRAPH, or similar.

Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).

Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward.

Experience working and communicating cross functionally in a team environment.