Staff Research Engineer - Interactive Avatars

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US.

As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations.

Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow.

About the role

As a Staff Research Engineer, you will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on avatar-centric interactive video diffusion models. Within the team you’ll have the opportunity to work on the applied side of our research efforts and directly impact our solutions that are used worldwide by over 60,000 businesses.

This is a unique opportunity for experts in machine learning and diffusion models to shape the future of AI video agents that can think, act, and react like humans. As part of our Interactive Avatars Team, you’ll work on cutting-edge research with a clear focus on turning breakthrough ideas into real product capabilities. You’ll join a team that moves fast, iterates often, and builds models that ship and make a meaningful impact. Example tasks and responsibilities include:

Adapt diffusion models to incorporate diverse conditioning signals (e.g., audio, motion, interaction cues).

Develop methods for streaming infinitely long video sequences at real-time rates.

Work on the perceptual layer of interactive agents, including understanding user audio and generating appropriate contextual reactions.

Improve lip-sync accuracy, motion realism, and overall visual quality in video diffusion models.

Build robust evaluation frameworks and test suites to enable continuous quality tracking.

Collaborate closely with our data team to define data needs and ensure high-quality datasets.

Stay up to date with research in world models, interactive human/agent modeling, diffusion models, and related areas.

What we're looking for:

Comfortable owning and executing on the responsibilities listed above.

Strong ML (e.g., diffusion, GANs, VAEs) and computer vision background with relevant industry experience.

Hands-on experience with diffusion models (ideally avatar-centric or video-focused) and up to date with recent advances.

Proficient in PyTorch and familiar with modern ML frameworks and tooling.

Strong Python engineering skills, confident with git and version control, and a commitment to clean, maintainable research code.

Outcome-driven, detail-oriented, and motivated to push state-of-the-art research into real product impact.

Clear communicator of hypotheses, experiments, and results.

What will make you stand out:

Experience with audio-conditioned video diffusion models and deep knowledge of recent video DiT architectures.

Demonstrated ability to own the full model development pipeline end to end, from data preparation to model design, training, and evaluation.