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.
The opportunity
At Synthesia we really care about video generation, especially about human centric avatar video generation. This led us to release models such as EXPRESS-Video, and soon our latest video model - these are the best avatar video models in the world, and we are committed to continuing and double down our efforts in leading that area. Our goal is to get to human centric video models that can generate arbitrary long videos at high resolution with arbitrary actions and events. That means continuously training large generative video models from scratch with the proprietary data pipelines and compute infrastructure to support it at scale. We are looking for a technical leader who owns the full stack end-to-end, someone who bridges pre-training and post-training, sets long-term direction alongside research leadership, and is personally present at the hardest parts of the work. If building foundation model capability from the ground up at a company genuinely committed to leading the field sounds like the right next challenge, this role was written for you.
About the role
Synthesia's video generation capability is core to everything we ship. It involves roughly 15 people working daily across pre-training and post-training stages, and the complexity of coordinating across those stages, at the scale of compute and data we now operate, requires a different kind of technical leadership.
We're looking for a Principal Research Engineer (L7) to own the full technical stack for offline video generation. This is a senior individual contributor position with outsized scope and influence. You'll partner directly with research leadership and team leads to define long-term strategy, resolve the hardest cross-cutting technical problems, and raise the bar for how quickly research reaches product.
The person we're looking for has trained large generative models from scratch, not supervised it from a distance, but done it, debugged it, and shipped it. More than that, they're driven by a genuine ambition to push what's possible in video generation, and they care deeply about seeing that work land in product and reach users.
What you'll do
Own the end-to-end technical direction for offline video generation, spanning pre-training and post-training, resolving the artificial boundary between those two stages in service of shipping better models faster.
Partner with research leadership and team leads to define a unified long-term roadmap, broken into achievable objectives, and drive execution against it.
Identify the most critical technical gaps across the video generation pipeline and jump in to unblock them, whether that means architectural decisions, training stability, post-training alignment, or cross-team coordination.
Increase the velocity at which research ships to product: accelerate problem-solving, improve research-to-production handoffs, and increase visibility of research output in partnership with PMs.
Coach and elevate more junior researchers and engineers toward senior technical thinking and execution.
Help shape team structure and refine processes to enable high-velocity, cohesive execution across research.
You'll thrive in this role if you have
A proven track record training large-scale video generation models from scratch, across multiple nodes, at the scale of millions of hours of data.
Deep experience with post-training techniques at scale: RLHF, GRPO, DPO, and the judgment to know when and how to apply them.
A proven track record data quality and you are not reluctant to question it.
The ability to think strategically about multi-year research direction and execute hands-on at the frontier of what the team is building.
Strong cross-functional influence: you shape how teams work together without needing positional authority to do it.
A leadership style grounded in technical involvement. You lead by example, inspire through craft, and communicate with clarity.
Genuine hunger to unlock new capabilities and an obsession with shipping. You're not satisfied by research that stays in a notebook. You want it in the hands of users.
Particularly relevant experience
Having owned a major model generation or capability jump end-to-end, from training runs through to product deployment.
Working across both pre-training and post-training stages on the same model family, with direct accountability for the outcomes of both.
Experience operating at scale: large distributed training runs, significant compute budgets, and multi-million hour data pipelines.
Applying alignment and fine-tuning techniques in a video or multimodal context, not just text.
Experience with human feedback pipelines applied to generative video or audio.
Leading or significantly influencing the technical direction of a research team while remaining hands-on.
Dealbreakers
We will not be a good fit if you prefer to lead without staying technically involved, or if clear and direct communication across research and product isn't one of your strengths. This role requires presence at the frontier of the work, not above it. And if shipping doesn't excite you as much as the research itself, this probably isn't the right role.
