Generative Video Scientist: Realistic Digital Humans

Responsibilities:

• Conduct research and develop models to advance the state-of-the-art in generative computer vision technologies, with a focus on creating highly realistic digital faces and bodies.

• Strive to set new standards in the realism of digital human appearance, movement, and personality, ensuring that generated content closely resembles real-life scenarios.

• Implement techniques to achieve high-quality results in zero-shot or few-shot settings, as well as customized avatars for different use cases while maintaining speed and accuracy.

• Develop innovative solutions to enable comprehensive customization of video content, including the creation of digital people, modifying scenes, and manipulating actions and speech within videos.

Preferred Qualifications:

• PhD in computer science (or related field) or 3+ years of industry experience

• Strong academic background with a focus on computer vision and transformers, specializing in NeRFs, GANs, Diffusion, Gaussian Splatting, or related areas.

• Publication Record:
  Highly relevant publication history, with a focus on generating or manipulating realistic digital faces, bodies, expressions, body movements, etc. Ideal candidates will have served as the primary author on these publications.

• Expertise in Deep Learning:
  Proficiency in deep learning frameworks such as Tensor Flow, PyTorch, or similar, with hands-on experience in designing, training, and deploying neural networks for multimodal tasks.

• Strong understanding of Computer Science fundamentals (algorithms and data structures).

Benefits:

• Comprehensive medical, dental, and vision plans

• Anything you need to do your best work

• We’ve done team off-sites to places like Paris, London, Park City, Los Angeles, Upstate NY, and Nashville with more planned in the future.

Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.