Research Scientist, 3D Computer Vision & Machine Learning (PhD)

Research Scientist, 3D Computer Vision & Machine Learning (PhD) Responsibilities Lead, collaborate, and execute on research that pushes forward the state of the art in 3D computer vision, multimodal reasoning and generative approaches. Directly contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results. Work with the team to help design, setup, and run practical experiments and prototype systems related to large-scale, long-duration sensing and machine reasoning. Contribute to publications and open-sourcing efforts. Help identify long-term ambitious research goals as well as intermediate milestones. Mentor other team members. Play a significant role in healthy cross-functional collaboration. Minimum Qualifications Experience communicating research for public audiences of peers. Experience with real world system building and data collection, including design, coding (C++) and evaluation (C++/Python), including experience with modern ML methods and algorithms. Hands-on experience implementing 3D computer vision algorithms and training/evaluating ML and AI models. Currently has or is in the process of obtaining a PhD in the field of Computer Vision, Computer Science, Mathematics, a related field, or equivalent practical experience. Degree must be completed prior to joining Meta. Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment. Experience in developing and debugging in C/C++, Python, or C#. Research experience in 3D ML and AI research, specifically around Object Tracking / Detection / Segmentation, 3D semantic scene understanding, or generative 3D scene modeling. Preferred Qualifications Experience working in a Unix environment. 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 diverse points of view to determine a path forward. Experience working and communicating cross functionally in a team environment. 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, NeurIPS, ECCV, ICCV, IROS, ICRA, or similar.

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