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.
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.