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
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
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