Staff Machine Learning Engineer – Pricing

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Take full ownership of essential elements of the dynamic pricing system from design to production operation.

• Identify the best strategies to minimize sales adjustments and validate their effectiveness.

• Ensure components are observable, secure, and can be replayed to catch incorrect pricing before reaching customers.

• Facilitate seamless delivery across engineering, platform, and commercial teams.

• Manage components such as models that learn from both successful and unsuccessful deals, experimentation and measurement frameworks, and live pricing guardrails.

• Design experiments and holdouts for low-volume, high-value transactions where standard A/B testing may not be feasible.

• Establish monitoring, alerting, guardrails, and phased releases.

• Identify drift, runaway feedback loops, and unexpected price fluctuations that require review.

• Ensure pricing decisions are reproducible for debugging and regulatory purposes.

• Collaborate with the Price Quoting team and ML Platform to develop production-ready models.

• Investigate the reasons behind sales team price adjustments and transform those insights into model inputs or new strategies.

• Clarify model behavior and trade-offs to colleagues in engineering, product, and commercial sectors.

• Redesign ongoing pricing workflows utilizing AI, including feedback triage, daily price assessments, and experiment documentation, determining which processes should remain human-operated.

• Report to the ML Leader for Rosso.

⛳️ Requirements

• The majority of your current responsibilities involve writing and deploying production code; this role does not focus on people leadership or architecture where others execute.

• Proven experience managing a live ML system that makes automated decisions involving financial implications, such as algorithmic trading, dynamic pricing, marketplaces, ad bidding, credit, or betting.

• Experience dealing with production failures, including feedback loops, silent drift, undesired outputs reaching customers, and rollbacks.

• Strong skills in probabilistic modeling and decision-making under uncertainty, including pricing, conversion, elasticity modeling, and experimentation.

• Ability to define problems from first principles and choose the most straightforward and effective approach.

• Experience operating ML production services on contemporary cloud infrastructure, including containerized models behind APIs, event-driven microservices, infrastructure as code, and CI/CD on AWS or similar platforms.

• Proficiency in production-grade Python.

• Experience designing for observability, testing, and replay capabilities.

• Capability to collaborate effectively as a peer with software engineers.

• Proven record of influencing a commercial metric alongside product managers and commercial stakeholders.

• Utilizes AI tools as a daily work enhancer and understands their limitations.

• Experience in the energy sector is not mandatory.

• Bonus: experience in energy, commodities, or markets where pricing, forecasting, and risk interplay.

• Bonus: familiarity with contextual bandits, causal inference, or Bayesian methods applied in production.

• Bonus: knowledge of stochastic optimization or operations research.

• Bonus: PhD in mathematics, physics, computer science, or operations research.

• Fluent in speaking, reading, and writing English.

🏝️ Benefits

• Stock Options: every team member has a stake in our mission.

• 25 days of holiday plus public holidays.

• Option to exchange public holidays for those that are most significant to you.

• Additional day off to celebrate your birthday.

• Fully remote work arrangement, distributed across Europe.

• Up to £1,200 / €1,200 annually for remote setup, co-working passes, equipment, etc.

• Up to £150 / €150 monthly wellness budget for therapy, gym memberships, meditation apps, etc.