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 roleAs a Senior 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.
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.
A strong publication record in areas such as world models, interactive agents, or video diffusion models.
Attractive compensation
Hybrid work setting with an office in London, Zurich, and Munich
25 days of annual leave + public holidays
Work in a great company culture with the option to join regular planning and socials at our hubs
A generous referral scheme when you know people that are amazing for us
Strong opportunities for your career growth
You can see more about Who we are and How we work here: https://www.synthesia.io/careers
Skills Required
- Strong machine learning and computer vision background with relevant industry experience
- Hands-on experience with diffusion models
- Proficiency in PyTorch and familiarity with modern machine learning frameworks and tooling
- Strong Python engineering skills
- Confidence with Git and version control
- Ability to write clean, maintainable research code
- Ability to own and execute the listed responsibilities
- Clear communication of hypotheses, experiments, and results
- Experience with audio-conditioned video diffusion models and video DiT architectures
- Ability to own the full model development pipeline from data preparation through evaluation
- Strong publication record in world models, interactive agents, or video diffusion models
Synthesia Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Synthesia and has not been reviewed or approved by Synthesia.
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Leave & Time Off Breadth — Leave benefits are positioned as generous, including substantial annual leave plus public holidays and an additional long-tenure sabbatical with a cash award. Flexible working hours and hybrid/remote arrangements further strengthen perceived time-off and flexibility value.
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Healthcare Strength — Health coverage is described as robust, including private medical insurance with mental health support and dental/vision coverage. Added features like cashback options and gym discounts extend the package beyond basic medical coverage.
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Equity Value & Accessibility — Equity is framed as a meaningful part of total rewards through a generous stock options plan and a recent employee liquidity event tied to a major funding round. This can materially improve the perceived value and accessibility of long-term incentives versus options that remain purely paper value.
Synthesia Insights
What We Do
Synthesia is the #1 rated AI video communications platform. Thousands of companies use it to create videos in 140 languages, saving up to 80% of their time and budget. ? Trusted by Zoom, Xerox, Teleperformance, Amazon and mor
