Research Scientist Manager - 3D Generative AI

Meta Reality Labs brings together R&D team of researchers, developers, and engineers with the shared goal of developing AR and VR across the spectrum.

The Core-AI group in Reality Labs is seeking a technical leader to join our team to solve the next generation of research challenges on the path to building the 3D Metaverse.

The aim of this role is to develop and advance state of the art research in 3D Generative AI technologies such as generating objects, materials, animation and worlds.

Responsibilities:

Research Scientist Manager - 3D Generative AI Responsibilities:

Grow a team of domain experts within 3D Generative AI

Develop technical vision, long-term strategy and set direction for the team and the organization

Drive execution of developing models and systems that are crucial to the end user experience

Communicate, collaborate, and build relationships with customers and peer teams to facilitate cross-functional projects

Remain up-to-date on ongoing software development activities in the team, help work through technical challenges, and be involved in design decisions

Be hands-on supporting and leading teams of software engineers and research scientists

Qualification and experience:

Minimum Qualifications:

PhD in the field of computer vision, robotics, ML or equivalent

Background in generative-ai, 3D computer vision, video and image generation.

Experience designing machine learning algorithms, including experience creating software for data loading, training, and inference of novel ML architectures

Experience with cross functional collaboration with product and platform teams, as well as non-engineering functions

Demonstrated experience recruiting, building, structuring, leading technical organizations, including performance management

Preferred:

Preferred Qualifications:

Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as CVPR, ECCV/ICCV, NeurIPS, ICLR, SIGGRAPH

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

Mathematical background and understanding of numerical optimization, linear algebra, probabilistic estimation and 3D geometry