ML Engineer (Routing)

Andersen is hiring an ML Engineer (Routing) for a project developing machine learning solutions for real-time routing optimization, ETA prediction, and large-scale geospatial data processing.

The customer is a global investment management firm providing tailored investment solutions to institutional and private clients. It combines financial expertise with long-term investment strategies to help clients achieve their objectives while adapting to changing market conditions. The organization focuses on innovation, responsible investing, and operational excellence, continuously enhancing its capabilities to deliver sustainable value and support long-term growth.

The project is focused on developing machine learning solutions to improve ETA accuracy and routing quality at a scale. It includes building production-grade ML models, processing large-scale geospatial data, and deploying low-latency inference systems for real-time routing optimization.

Responsibilities:

• Designing and building ML models that correct and refine the routing engine's ETA estimates, from gradient-boosted trees through to neural and Transformer-based architectures as data scale grows.

• Developing traffic-estimation models that turn large-scale GPS data into road-level speeds and historical-traffic profiles and feed them into the routing engine to produce time-of-day-aware ETAs.

• Working on map-matching that snaps noisy GPS data onto the road graph, and the spatial aggregations that make movement and speed data usable for modeling.

• Improving ETA calculation, smoothing, and rerouting logic to close the gap between predicted and actual arrival times across changing conditions.

• Translating routing and ETA goals into ML objectives with the right proxy metrics and non-functional requirements, including loss formulations where under- and over-prediction carry different costs.

• Leading evaluation end-to-end, from offline accuracy and routing-quality metrics to the design of online…