AI / Data Engineer - Route Intelligence
Summary
Builds the AI layer for WasteHero's waste-collection platform: designing ML models and data pipelines for fill-level forecasting, dynamic routing and anomaly detection, plus LLM-based assistants for operations teams. Core stack is Python, SQL, dbt/Spark-style pipelines and cloud ML tooling.
Waste collection is a routing and forecasting problem at city scale. WasteHero's platform already plans routes and fleet for municipalities and haulers in six countries; we are now building the AI layer on top: fill-level forecasting, dynamic routing, anomaly detection and an AI assistant for operations teams.
What you will do
- Design and ship models and data pipelines that turn collection, container and vehicle data into better routes and fewer missed pickups.
- Build the evaluation and monitoring around them so customers can trust the numbers.
- Work with our engineers to put LLM-based assistants into daily operations workflows, with guardrails.
- Partner with implementation teams on real municipal data, warts and all.
What we look for
- 3+ years in applied ML or data engineering with production deployments.
- Strong Python; comfortable with SQL, dbt/Spark-style pipelines and cloud ML tooling.
- Experience with optimisation (VRP, scheduling) or time-series forecasting is a strong plus.
- Pragmatic: you pick the simplest model that moves the operational metric.
Why WasteHero
A rare dataset (millions of collections across countries), a clear KPI (kilometres, missed pickups, complaints) and customers who deploy what you build. Remote-friendly across Europe; Aarhus is home base.
WasteHero is an equal opportunity employer.