Who are we?
From your everyday PowerPoint presentations to Hollywood movies, AI will transform the way we create and consume content.Today, people want to watch and listen, not read — both at home and at work. If you’re reading this and nodding, check out our
brand video.
Despite the clear preference for video, communication and knowledge sharing in the business environment are still dominated by text, largely because high-quality video production remains complex and challenging to scale—until now….
Meet Synthesia
We're on a mission to make video easy for everyone. Born in an AI lab, our AI video communications platform simplifies the entire video production process, making it easy for everyone, regardless of skill level, to create, collaborate, and share high-quality videos. Whether it's for delivering essential training to employees and customers or marketing products and services, Synthesia enables large organizations to communicate and share knowledge through video quickly and efficiently. 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.
In 2023, we were one of 7 European companies to reach unicorn status. In February 2024, G2 named us as the fastest growing company in the world. In 2025 we announced our series D funding. In total we’ve raised over $330M in funding from top-tier investors, including NEA, Atlassian Ventures, WiL, PSP Growth, and existing investors such as Accel, Nvidia, Kleiner Perkins, GV and top founders and operators including Stripe, Datadog, Miro, Webflow, and Facebook.
What will you be doing?
The Data team owns the entire lifecycle of data for researchers. From sourcing, to processing and storage. They provide the data bundles required for the research teams to train their model at scale.As part of the Data team, you'll be working with over a million hours of video and audio data. You'll be scaling open-source models, building systems that enable us to efficiently query data in our lake, and optimise deep learning pipelines in production. This isn't a classic data engineering role; it's more of a hybrid between ML infra and research engineering, owning pipelines that directly impact cutting-edge AI research and enabling our entire R&D department to conduct their work more efficiently. The nature of audio and video data brings unique challenges.
Your work will enable us to better overcome edge case videos (such as those with large resolutions, or long durations) and more effectively identify the useful elements of a video, from one person in frame through to the emotional performance.
Who are you?
- Background in Computer Science, Computer Vision, or Audio ML
- Experience working in deep learning teams and production environments
- Strong Python skills and a passion for clean, maintainable code
- Hands-on experience with workflow orchestration (we use Kubeflow and Spark)
- Interest in large-scale, non-tabular data (video, audio, images)
Bonus points if you have experience in:
- Audio domain - such as TTS, emphasis prediction, or transcription
- Video domain - such as transcoding or downscaling
- Model optimisation experience e.g. GPU utilisation, CPU/GPU concurrent workloads
The good stuff...
- Very competitive compensation (salary + stock options + bonus)
- Hybrid work setting with an office in London, Amsterdam, 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
- A generous referral scheme when you know people that are amazing for us
- Strong opportunities for your career growth
- + other benefits depending on your location
You can see more about who we are and how we work here: https://www.synthesia.io/careers#LI-MD1
