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Staff Research Scientist- Interactive Avatars

at Synthesia

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May require office time No longer listed on its source board ● Posted yesterday Europe Data

About this role

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 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.

Why join us?

We’re living the golden age of AI. The next decade will yield the next iconic companies, and we dare to say we have what it takes to become one. Here’s why,

Our culture

At Synthesia we’re passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions. Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here.

Serving 50,000+ customers (and 50% of the Fortune 500)

We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2.

Proprietary AI technology

Since 2017, we’ve been pioneering advancements in Generative AI. Our AI technology is built in-house, by a team of world-class AI researchers and engineers. Learn more about our AI Research Lab and the team behind.

AI Safety, Ethics and Security

AI safety, ethics, and security are fundamental to our mission. While the full scope of Artificial Intelligence's impact on our society is still unfolding, our position is clear: People first. Always. Learn more about our commitments to AI Ethics, Safety & Security.

The good stuff...

  • Competitive compensation

  • Hybrid work setting with an office in London, Zurich, Munich, or remote in Europe.

  • 25 days of annual leave + public holidays

  • Great company culture with the option to join regular planning and socials at our hubs

  • + other benefits depending on your location

You can see more about Who we are and How we work here: https://www.synthesia.io/careers

Real Remote Score 53/100 · see the full breakdown

Real Remote Score

53/100

Mixed

Comp
0/25
Location
15/25
Source
10/15
Clarity
8/15
Freshness
20/20
Why this score? ▾
  • Compensation · No salary disclosed 0/25
  • Location · Continent-scoped (EU / APAC / Americas) 15/25
  • Source · Remote-first job board 10/15
  • Role clarity · Seniority clear, stack not in title 8/15
  • Freshness · Posted yesterday 20/20

How the Real Remote Score is calculated → · Score appeals & corrections

Hybrid Transparency Score 35/100 · see the full breakdown

Hybrid Transparency Score

35/100

Weak

Days
0/30
Location
30/30
Schedule
0/15
Relocation
0/15
Source
5/10

This role is hybrid: it expects some in-office presence. HTS grades how clearly the employer discloses the hybrid terms. How the Hybrid Transparency Score works →

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