Darum lohnt es sich
Why this role is exciting You’ll build production-grade ML systems that run continuously - not just notebooks Your work powers real-time decisioning across massive behavioural datasets True autonomy: low bureaucracy, high trust, modern engineering culture Close collaboration with applied AI, engineering, and product You get startup-like ownership backed by the stability of a well-established tech group This platform represents the future of how digital products decide and adapt at scale What you’ll do Build end-to-end ML models for user profiling, recommendations, sorting, and incentives Use frameworks like scikit-learn, PyTorch , and GPU-accelerate If you want to build AI systems that make decisions in real time — not just produce offline predictions - this role is genuinely rare.
This company has built a next-\u201c\u201d decisioning platform that interprets behaviour at scale and takes hundreds of automated decisions every second . Their models transform raw behaviour signals into real-\u201c\u201d scores that drive personalised rankings, recommendations, and user experiences across millions of journeys.
You’ll be working with cutting-\u201c\u201d ML, real-\u201c\u201d inference, Azure ML pipelines, and a high-speed production environment where your work directly shapes the outcomes users see.
