Logistics AI Engineer; Backend

This logistics technology company is rethinking how freight moves globally. They work with some of the world's largest shippers and carriers, using AI to optimise routes, predict delays, and reduce the staggering inefficiency that plagues global supply chains. The numbers are eye-watering: billions in wasted fuel, millions of empty miles driven, mega tonnes of unnecessary emissions. They need an AI Engineer to build the systems that make logistics intelligent.

You’ll work on route optimisation, demand forecasting, carrier matching, and real-time replanning when things go wrong (and in logistics, things always go wrong). The problems are combinatorially hard, the data is messy, and the stakes are real. The team is a mix of logistics veterans and tech talent from Uber, Amazon, and Deep Mind. They’ve just raised a Series B and are scaling aggressively.

If you want to work on AI that has immediate, tangible impact on the physical world, this is the place.

• Build AI systems for route optimisation, load planning, and carrier matching
• Design real-time replanning systems that respond to delays, disruptions, and changing conditions
• Create demand forecasting models that predict shipment volumes and capacity needs
• Build the data pipelines and feature stores that power ML models at scale
• Work with operations teams to understand the messy reality of how logistics actually works
• Optimise for the metrics that matter: cost, time, reliability, and carbon

• A strong backend engineer with 4+ years of experience, ideally with ML systems exposure.
• Experience with optimisation problems — vehicle routing, scheduling, or similar combinatorial challenges.
• Comfortable with Python and production ML tooling.
• Strong data engineering skills — you can build the pipelines that feed the models.
• Pragmatic about what AI can and can't do — you know when to use ML and when a heuristic will do.
• Excited by hard, real-world problems with tangible impact