Machine Learning Engineer, Pricing Optimisation

The Problem You'll Own:

• Pricing is one of the most direct levers on revenue in a marketplace.
• You'll own the algorithm end-to-end: understanding how users respond to price and modelling willingness to pay.
• The impact of your work will be measurable from day one.

Responsibilities:

• Monitor deployed models for data drift, distribution shifts, and degradation; own observability and alerting.
• Contribute pricing-relevant features to the feature store — user price sensitivity signals, historical purchase behaviour, category-level demand indicators.
• Work with Data Platform and Backend Engineering to ship pricing models as low-latency APIs integrated into live marketplace surfaces.

Requirements:

• Hands-on production experience building models that optimise pricing decisions — promotional pricing, demand-based pricing, or personalised pricing.
• End-to-end ML ownership — you've taken models from raw data through feature engineering, training, evaluation, API deployment, and production monitoring.
• Strong Python and MLOps fluency — extensive Python for model development, plus experience with MLOps tooling (MLflow or similar) for experiment tracking, model versioning, and lifecycle management.