Staff Research Scientist- Interactive Avatars

About The Role

As a Staff Research Scientist, you will join a team of 40+ researchers and engineers in our R&D department, working on the frontier of generative AI with a focus on avatar-centric, interactive video diffusion models.

This is a unique opportunity for experts in machine learning and diffusion models to shape the future of AI video agents that listen, respond, and react like humans. As part of our Interactive Avatars team, you'll build models that hold natural, real-time conversations: understanding what a user says and how they say it, then responding with appropriate turn-taking, backchannels, gaze, and facial and body reactions. You'll join a team that moves fast, iterates often, and turns breakthrough research into product capabilities that ship.

What You'll Do

• Set the research direction and roadmap for dyadic interaction modeling, balancing long-term bets with near-term product impact.
• Advance the state of the art in the perceptual layer of interactive agents, including understanding user audio and video and generating contextually appropriate reactions.
• Post-train multimodal models to generate rich, natural dyadic interactions from user audio and video inputs.
• Adapt diffusion models to new conditioning signals, such as conversational state, turn-taking, and listener cues.
• Build robust evaluation frameworks and test suites for continuous tracking of interaction quality.
• Partner with our data team to define data needs and shape high-quality datasets.
• Lead and mentor a small group of researchers, and drive technical decisions across research, data, and engineering.

What We're Looking For:

• Deep ML expertise and extensive hands-on experience with diffusion models, ideally for video or avatar generation.
• A strong publication record at top-tier venues (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, SIGGRAPH) in areas such as world models, dyadic interaction, or video diffusion, or equivalent demonstrated impact.
• Experience leading a small team of researchers and mentoring junior members.
• A track record of taking research from idea to production.
• Proficiency in PyTorch and modern ML tooling for large-scale training.
• Clear communication of hypotheses, experiments, and results, and the ability to influence direction across teams.

Nice To Have

• Experience with real-time or streaming generation, including autoregressive video diffusion.
• Distillation or other techniques for low-latency inference.
• Audio-driven facial, gesture, or full-body motion modeling.
• Conversational modeling, such as turn-taking, backchanneling, or listener-response generation.