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Research Scientist (diffusion)

Genmo 路 San Francisco HQ

Extracted from the posting

Base
Not stated
Remote
Bay Area (San Francisco); candidates near Bay Area or open to relocation
Visa
E-Verify company
Stack
PyTorch, TensorFlow, Python

Research Scientist working on text-to-video diffusion models, covering visual quality, temporal consistency, and semantic fidelity. Requires a PhD, a publication record in top conferences (CVPR, ICCV, NeurIPS, ICML), and PyTorch or TensorFlow experience. The role is based in San Francisco Bay Area.

We are Genmo, a research lab developing the world鈥檚 most sophisticated video world models to understand, simulate, and interact with the physical world. Our mission is to unlock the right brain of AGI. Join us in advancing physical intelligence and enabling robots to learn and act in a changing world.

Role overview:

We are seeking an exceptional Research Scientist to join our team, focusing on developing cutting-edge diffusion models for text-to-video generation. In this role, you will be at the forefront of innovation, creating novel architectures and algorithms that transform written descriptions into stunning, coherent video content.


Key responsibilities:

  • Lead research initiatives in advanced diffusion models for text-to-video generation, focusing on improving visual quality, temporal consistency, and semantic fidelity
  • Develop and implement state-of-the-art algorithms for translating textual descriptions into dynamic video content
  • Design and conduct rigorous experiments to validate new ideas and evaluate model performance
  • Collaborate with cross-functional teams to integrate research breakthroughs into our production pipeline
  • Stay at the cutting edge of the field by regularly reviewing academic literature and attending top-tier conferences
  • Contribute to the research community through high-quality publications and open-source contributions
  • Mentor junior researchers and foster a culture of innovation within the research team
  • Work closely with product teams to align research directions with user needs and market opportunities


Qualifications:

  • Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field
  • Must have:Strong publication record in top-tier conferences (e.g., CVPR, ICCV, NeurIPS, ICML) with a focus on generative models, particularly diffusion modelsExtensive experience implementing and optimizing large-scale generative models for image or video tasksDeep understanding of state-of-the-art techniques in text-to-image and text-to-video generationProficiency in Python and deep learning frameworks such as PyTorch or TensorFlowExcellent communication skills with the ability to explain complex technical concepts to diverse audiencesProven ability to work collaboratively in a team environment
  • Ideal candidate will have:Postdoctoral or industrial research experience in generative AI for videoHands-on experience with text-to-video generation projectsExpertise in other generative model architectures (e.g., GANs, VAEs) and their applications to videoExperience working with large-scale datasets and distributed computing environmentsTrack record of successful collaboration with product teams on technology transfersFamiliarity with video codecs, compression techniques, and perceptual quality metricsContributions to open-source projects in the field of generative AI


Additional information

The role is based in the Bay Area (San Francisco). Candidates are expected to be located near the Bay Area or open to relocation.

Genmo is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law. Genmo, Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish.

Technologies

PyTorchTensorFlowPython
Genmo
Genmo
Website

Job details

TypeFull-time
Work ModeOn-site
LevelSenior
Location馃嚭馃嚫San Francisco, CA
PostedNov 06, 2026
Apply Now

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