About the job
About Tavus
Tavus is at the forefront of innovation in human computing. Our mission is to develop AI Humans: an advanced interface that bridges the gap between individuals and machines, eliminating the friction found in current technologies. Our state-of-the-art human simulation models empower machines to see, hear, respond, and even exhibit realistic appearances—facilitating genuine, face-to-face interactions. AI Humans integrate the emotional insight of humans with the scalability and dependability of machines, making them reliable agents accessible 24/7, in any language, on our terms.
Imagine having access to an affordable therapist, a personal trainer that fits your schedule, or a team of medical assistants dedicated to providing personalized care for every patient. With Tavus, individuals, enterprises, and developers have the tools to create AI Humans that connect, comprehend, and act with empathy on a large scale.
We are a Series A company supported by esteemed investors such as Sequoia Capital, Y Combinator, and Scale Venture Partners.
Join us in shaping a future where machines and humans genuinely understand one another.
The Position
We are seeking an AI Researcher to join our core AI team and advance the frontiers of multimodal conversational intelligence. If you excel in dynamic environments, enjoy transforming abstract concepts into functional code, and derive motivation from pushing the boundaries of possibility, this role is designed for you.
Your Responsibilities
Engage in research focusing on Foundational Multimodal Models specifically in the realm of Conversational Avatars (such as Neural Avatars and Talking-Heads).
Develop models for video, audio, and language sequences utilizing Autoregressive and Predictive Architectures (e.g., V-JEPA) and/or Diffusion methodologies, with a focus on temporal and sequential data rather than static images.
Collaborate closely with the Applied ML team to implement your research into production systems.
Remain at the forefront of multimodal learning and assist us in defining what “cutting edge” will mean in the future.
Ideal Candidate Profile
PhD (or nearing completion) in a relevant field, or equivalent practical research experience.
Experience in multimodal machine learning, particularly focused on conversational interfaces.

