Company Description Cint is a pioneer in research technology (ResTech).
Our customers use the Cint platform to post questions and get answers from real people to build business strategies, confidently publish research, accurately measure the impact of digital advertising, and more.
The Cint platform is built on a programmatic marketplace, which is the world's largest, with nearly 300 million respondents in over 150 countries who consent to sharing their opinions, motivations, and behaviours.
The immediate focus is supporting the Synthetic Data Platform — models for survey augmentation and respondent profiling — but the role's longer-term remit is broader: Trust Score (our respondent quality and fraud detection model) and other AI/ML initiatives need the same platform capabilities.
You'll start by reviewing the current setup and deciding whether to extend it or rebuild parts of it, then build out the shared AI/ML platform from there.
The Team You'll report into our Infrastructure and Data Engineering organisation, working in close partnership with the AI/ML team in Prague.
This is deliberately a platform-with-feature-focus role: your day-to-day delivery serves the Synthetic Data team's needs, but your architectural remit covers all of Cint's AI/ML workloads.
Decide what's worth building on and what needs to be rebuilt.
Make the call and own the rationale.
Build the shared AI/ML platform: Training infrastructure, experiment tracking, model registry, serving, monitoring.
Built once, used by Synthetic, Trust Score, and whatever comes next.
Oversee the full ML lifecycle: From data ingestion and feature processing to annotation workflows, ensuring the platform facilitates frictionless, rapid model iteration for Data Scientists.