Research Scientist (diffusion)
@ GenmoResearch Scientist (diffusion)
About the job
Genmo is an AI research lab focused on building open models for video generation, unlocking creative AI. We seek a researcher to develop advanced diffusion models for text-to-video and contribute to cutting-edge innovations in video synthesis.
Requirements
- Strong publication record in top-tier conferences
- Experience in generative models for image/video
- Proficiency in Python and deep learning frameworks
- Excellent communication skills
- Ability to collaborate in teams
Qualifications
- Ph.D
- in Computer Science or related field
- Postdoctoral or industrial research experience
- Hands-on experience with text-to-video projects
- Knowledge of large-scale datasets
Full job description
We are Genmo, a research lab dedicated to building open, state-of-the-art models for video generation towards unlocking the right brain of AGI. Join us in shaping the future of AI and pushing the boundaries of what's possible in video generation.
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 models
Extensive experience implementing and optimizing large-scale generative models for image or video tasks
Deep understanding of state-of-the-art techniques in text-to-image and text-to-video generation
Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
Excellent communication skills with the ability to explain complex technical concepts to diverse audiences
Proven ability to work collaboratively in a team environment
Ideal candidate will have:
Postdoctoral or industrial research experience in generative AI for video
Hands-on experience with text-to-video generation projects
Expertise in other generative model architectures (e.g., GANs, VAEs) and their applications to video
Experience working with large-scale datasets and distributed computing environments
Track record of successful collaboration with product teams on technology transfers
Familiarity with video codecs, compression techniques, and perceptual quality metrics
Contributions 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.
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