We are seeking a highly motivated Senior Diffusion Model Researcher to lead cutting-edge research in generative models with a focus on image and video diffusion. The ideal candidate combines deep theoretical understanding with strong practical experience in training and deploying large-scale generative models.
A day in the life and how youll make an impact:
Conduct state-of-the-art research on generative models, with an emphasis on diffusion techniques for image and video synthesis.
Design, implement, and evaluate novel architectures and training methodologies for scalable diffusion models.
Collaborate with cross-functional teams (engineering, product, design) to transition research into production-grade systems.
Publish results in top-tier conferences (e.g., NeurIPS, CVPR, ICCV, ICML) and contribute to open-source initiatives.
Stay up to date with the latest advancements in generative modeling and identify promising research directions.
Mentor junior researchers and help shape the AI research roadmap.
A day in the life and how youll make an impact:
Conduct state-of-the-art research on generative models, with an emphasis on diffusion techniques for image and video synthesis.
Design, implement, and evaluate novel architectures and training methodologies for scalable diffusion models.
Collaborate with cross-functional teams (engineering, product, design) to transition research into production-grade systems.
Publish results in top-tier conferences (e.g., NeurIPS, CVPR, ICCV, ICML) and contribute to open-source initiatives.
Stay up to date with the latest advancements in generative modeling and identify promising research directions.
Mentor junior researchers and help shape the AI research roadmap.
Requirements:
Ph.D. in Computer Science, Machine Learning, or a related field, or equivalent industry experience.
At least 5 years experience as algorithm developer or researcher
Proven track record in generative modeling, specifically diffusion-based models for image and/or video generation.
Strong proficiency in Python and deep learning frameworks such as PyTorch or JAX.
Solid understanding of probabilistic modeling, score-based generative methods, and denoising diffusion techniques.
Experience with large-scale model training and high-performance computing environments.
Publications in top AI/ML conferences or journals.
Preferred Qualifications:
Experience in latent diffusion, video generative models, or multi-modal generation (e.g., text-to-image/video).
Contributions to open-source generative modeling libraries.
Familiarity with model evaluation metrics and benchmarking protocols for generative content.
Prior experience in a startup or fast-paced R&D environment.
Ph.D. in Computer Science, Machine Learning, or a related field, or equivalent industry experience.
At least 5 years experience as algorithm developer or researcher
Proven track record in generative modeling, specifically diffusion-based models for image and/or video generation.
Strong proficiency in Python and deep learning frameworks such as PyTorch or JAX.
Solid understanding of probabilistic modeling, score-based generative methods, and denoising diffusion techniques.
Experience with large-scale model training and high-performance computing environments.
Publications in top AI/ML conferences or journals.
Preferred Qualifications:
Experience in latent diffusion, video generative models, or multi-modal generation (e.g., text-to-image/video).
Contributions to open-source generative modeling libraries.
Familiarity with model evaluation metrics and benchmarking protocols for generative content.
Prior experience in a startup or fast-paced R&D environment.
This position is open to all candidates.
