Research Scientist Intern, Generative AI (PhD) (multiple locations)

Meta

Greater London

Sur place

GBP 30 000 - 50 000

Plein temps

Il y a 3 jours
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Résumé du poste

Meta’s Reality AI Research team seeks a PhD student candidate for a Research Scientist Intern, Generative AI, across multiple locations. The role focuses on developing novel generative models for 3D/4D content, designing efficient architectures, and contributing work that advances Meta wearables and AI products.

You will drive cutting‑edge research, collaborate across teams, and aim for top‑tier publications while prototyping ideas and integrating them into large‑scale data and training

Qualifications

  • Currently a PhD student or in the process of obtaining a PhD in computer vision, computer graphics, machine learning, or a related field.
  • Hands‑on knowledge with state‑of‑the‑art model architectures (multi‑view transformers, diffusion/autoregressive models, etc.) for image, object, scene, or video reconstruction, understanding, generation.
  • Experience with PyTorch and Python.
  • Understanding of 3D geometry, statistical analysis of data, and mathematical modeling.
  • Excellent interpersonal and communication skills, cross-group and cross-culture collaboration.
  • High levels of creativity and quick problem solving capabilities.
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Responsabilités

  • Actively driving and participating in cutting edge research for 3D/4D scene reconstruction, understanding & generation.
  • Developing efficient deep neural network model architectures.
  • Contributing research that can be applied to Meta wearables and AI development.
  • Together with our team, work towards a top‑tier, scientific publication.

Connaissances

PhD in CV/graphics/ML
Strong problem solving
Excellent communication

Formation

PhD in computer vision / graphics / ML

Outils

PyTorch
Python

Description du poste

The Reality AI Research team explores, develops, and ships novel and cutting‑edge technologies for 3D/4D scene reconstruction, understanding and generation, serving as the foundation for future wearables and AI products. Our team is tackling a variety of technical challenges across the entire tech stack, including but not limited to model architecture development, data curation, and large‑scale model training. We're looking for candidates who share a passion for exploring and solving complex, challenging problems.We are looking for an exceptional PhD student with a proven track record in developing generative approaches for solving computer vision and graphics problems (e.g., conditional, generative models for videos or (dynamic) 3D content), as well as an outstanding software engineer who can efficiently prototype new ideas as well as integrate them into our large‑scale data and training infrastructure.

Research Scientist Intern, Generative AI (PhD) (multiple locations) Responsibilities
  • Actively driving and participating in cutting edge research for 3D/4D scene reconstruction, understanding & generation.
  • Developing efficient deep neural network model architectures.
  • Contributing research that can be applied to Meta wearables and AI development.
  • Together with our team, work towards a top-tier, scientific publication.
Minimum Qualifications
  • Currently has, or is in the process of obtaining a PhD in the field of computer vision, computer graphics, machine learning, or a related field
  • Hands‑on knowledge with state‑of‑the‑art model architectures (multi‑view transformers, diffusion/autoregressive models, etc.,for image, object, scene, or video reconstruction, understanding, generation, etc.)
  • Experience with PyTorch and Python
  • Understanding of 3D geometry, statistical analysis of data, and mathematical modeling
  • Excellent interpersonal and communication skills, cross-group and cross-culture collaboration
  • High levels of creativity and quick problem solving capabilities
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Preferred Qualifications
  • Intent to return to degree program after the completion of the internship/co‑op
  • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first‑authored publications at leading conferences (e.g., SIGGRAPH, CVPR, ECCV, ICCV, NeurIPS, ICLR, ICML) or journals (e.g., PAMI, IJCV, JMLR, ToG)
  • Experience with generative models (e.g., diffusion/autoregressive models), multi‑view transformers (e.g., VGGT, MapAnything), 3D/4D representations (point clouds, Gaussian Splatting), video generation (e.g. WAN/Cosmos), and inverse rendering techniques
  • Experience in 3D computer vision, graphics, and deep learning models for this domain
  • Demonstrated software engineer experience via previous internships, work experiences, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
  • Familiarity with AI native coding practices workflows
About Meta

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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