Applied AI Manager – Talabat

This role sits within Talabat, the Delivery Hero-owned on-demand food and q-commerce platform, working on applied AI initiatives likely covering areas such as demand forecasting, routing and dispatch optimization, personalization, or fraud detection – the kinds of problems that come with running a high-volume, on-demand delivery platform. Day to day, that means translating business problems into applied machine learning solutions, working with data science and engineering teams to deploy models into production, and measuring and iterating on model performance against real business KPIs.

This is applied rather than purely research-focused work: the value of a model here is measured by whether it actually moves business outcomes – faster deliveries, better forecasts, more relevant recommendations – not by its sophistication in isolation. A management dimension to the role suggests leading a small team or coordinating cross-functional AI initiatives rather than working purely as an individual contributor.

This suits an experienced applied AI or machine learning professional who wants to work on real-world, high-volume consumer platform problems rather than research for its own sake.

It’s a strong fit for someone who wants genuine production deployment experience at real consumer scale.

Talabat operates at genuinely massive scale across food delivery and q-commerce, and even small improvements in applied AI - better demand forecasting, smarter dispatch, more relevant recommendations - translate into meaningful efficiency and revenue gains across millions of orders. An Applied AI Manager's work directly shapes operational costs through delivery efficiency, customer experience through relevance and speed, and ultimately profitability at a platform this size. Because the role sits at the intersection of AI capability and real operational decisions, its impact is measured in actual business outcomes rather than research output alone, which is exactly the kind of accountability that makes applied AI roles at consumer-scale platforms especially high-leverage compared with similar roles at smaller companies. There's also a competitive angle worth naming: in a q-commerce market with several well-funded competitors, the platform with the sharper forecasting and more relevant recommendations tends to win marginal customer decisions more often, so applied AI work here isn't just an internal efficiency play, it's directly connected to how Talabat performs against its competitors.

Few roles offer the combination of applied AI depth and genuinely massive, real-time consumer data that a platform like Talabat provides, which makes this experience highly differentiated on a resume compared with applied AI work at smaller-scale companies. This is a strong platform toward senior AI or ML leadership, Head of Data Science, or Applied AI Director roles across any consumer tech or delivery platform afterward. Being part of the Delivery Hero group, a large global delivery conglomerate, also opens internal mobility across other markets and brands for AI professionals who want broader exposure later. The production-deployment focus of the role builds practical engineering credibility that pure research roles often lack, which matters increasingly as companies prioritize AI that actually ships and delivers measurable value over research prestige alone. There's also a market-timing angle worth naming: applied AI talent with genuine production deployment experience at consumer scale is in extremely high demand right now, and this kind of role, at this kind of scale, puts someone in a strong position to command senior compensation and seniority whenever they choose to make their next move. On top of that, applied AI experience earned at genuine consumer scale, rather than in a lab or pilot setting, is exactly the kind of proof point that distinguishes a strong AI resume from an average one in today's market.

• Strong experience in applied machine learning or AI, ideally with production deployment experience rather than research-only background
• Familiarity with problems common to on-demand delivery platforms, such as forecasting, optimization, or recommendation systems
• Experience managing or mentoring an applied AI or data science team, or leading cross-functional AI initiatives
• Strong communication skills translating technical AI work into business impact
• Degree in computer science, data science, machine learning, or a related field