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….

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. We’ve raised over $150M in funding from top-tier investors, including Accel, Nvidia, Kleiner Perkins, Google and top founders and operators including Stripe, Datadog, Miro, Webflow, and Facebook.

In this position, you will be joining the ML Platform Team to further develop our high-scale compute & data platform. Our team's goal is to super-charge the research teams to develop our AI models at scale as quickly and efficiently as possible. The team manages the entire cloud infrastructure and tooling that our researchers use to collect data & train the models at scale. 

In this role, you will initially mainly support our data platform efforts by provisioning, enriching & exposing new data to our research teams, while also providing appropriate tooling for them to leverage it during large model training. Additionally, you will collaborate with the researchers to make sure ML Engineering best practices are being followed.

• Background in Computer Science, ML Platform Engineering & (preferably) Data Engineering, with at least 3 years of industry experience
• You have processed / queried / used large volumes of data before, preferably in the Computer Vision domain
• You have experience setting up infrastructure at scale for ML / Data Teams, including CI/CD & Data pipelines
•  Experience with Workflow Orchestrators (such as Kubeflow, Argo, Dagster, Airflow etc.) is a big plus
• You have great coding skills in Python and you care about technical debt & documentation.
• You can find your way around a Kubernetes cluster and containerization is already second nature
• You have plenty of experience working with tooling from at least 1 major Cloud Provider (AWS, GCP, Azure)
• You get a lot of energy from collaborating with Researchers / Data Scientists to improve their day-to-day work
• And most importantly..You have excellent verbal and written communication skills in English and you are passionate about what you do!

• Attractive compensation  (salary + stock options + bonus)
• Hybrid work setting with an office in London, Amsterdam, Zurich, Munich, or remote
• 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, and company retreats
• 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