Logistics AI Engineer (Backend)

Vecta Ltd; Greater London; Hybrid; GBP 70,000 - 120,000; Full time

Job summary

Vecta Ltd is seeking an AI Engineer to design and build AI systems that optimise routes, forecast demand, and replan in real time when disruptions occur. The role combines backend engineering with production ML, tackling hard logistics problems with significant real-world impact.

You’ll work on route optimisation, load planning, and carrier matching, building data pipelines and feature stores to power scalable ML models while collaborating with operations teams to understand the messy realities

Qualifications

• 4+ years of backend engineering experience with a focus on ML systems
• Strong experience with optimisation problems (e.g., vehicle routing, scheduling)
• Proficient in Python and production ML tooling
• Solid data engineering skills and data pipelines

Responsibilities

• Build AI systems for route optimisation, load planning, and carrier matching
• Design real-time replanning systems that respond to delays and disruptions
• Create demand forecasting models for shipment volumes and capacity needs
• Develop data pipelines and feature stores powering ML models at scale
• Collaborate with operations to understand real-world logistics challenges

Skills

Backend engineering

ML systems exposure

Python

Data engineering

Optimization problems

Job description

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, megatonnes 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 DeepMind. 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