Staff Machine Learning Engineer - Pricing
Core
Design, build, and own key components of a dynamic pricing system that forecasts prices and volumes for energy transactions, ensuring safe automated decision-making with money attached.
Role type
Staff Machine Learning Engineer (L4)
Builds
Production ML models for dynamic pricing, experimentation layers, and live guardrails for the Rosso platform.
Domain
Energy trading and marketplaces
Deliverable
production ML models
Required skills
Probabilistic modelling, decision-making under uncertainty, production-grade Python, cloud infrastructure (AWS), CI/CD, observability, testing, replay, experimentation design, causal inference, stochastic optimisation
Preferred skills
Energy/commodities market experience, contextual bandits, Bayesian methods, PhD in maths/physics/CS/operations research
Technologies
Python, AWS, containerised models, event-driven microservices, APIs
Responsibilities
Own end-to-end delivery of dynamic pricing components; choose and validate competing bets to reduce sales adjustment; design experiments and holdouts for low-volume high-value deals; build monitoring, alerting, and staged release guardrails; explain model behaviour to stakeholders; redesign pricing workflows with AI.
