(Senior) Machine Learning Engineer, Revenue Management (m/f/d)

Description

The Revenue Management ML Engineering work in Lisbon, Team Orange, turns models into systems that set prices, forecast demand and steer a fleet of hundreds of thousands of vehicles, millions of times a day. You build these systems with Data Scientists, run them in production and help shape an ML platform that is still being built.

The company is a global mobility provider with revenue of €4.3 billion and around 9,000 employees. Its mobility platform combines car rental, car sharing, ride and chauffeur services, and car subscription, with access to a fleet of 360,000 vehicles, 4,000 cooperation partners and around 5 million drivers worldwide. Together with franchise partners it operates in more than 100 countries across 2,000 rental stations.

The team works from the Factory Lisboa hub in Beato and the ARTs Lisboa hub in Parque das Nações.

Responsibilities

• Build ML systems alongside Data Scientists, from the first design discussion through to validated results running in production.
• Own the design and architecture: how features are computed once and served consistently, how predictions reach consumers, and how training, serving and retraining connect.
• Release models safely through offline evaluation, shadow runs, champion/challenger comparisons and rollback plans, then operate what you release.
• Build quality into the system by defining what a healthy ML system looks like, automating checks and alerts, and tracing issues to their root cause so they do not return.
• Act as the link to MLOps: take the team's needs to the platform, bring platform standards back to the team, and co-own the templates and tooling that speed up the next use case.
• Raise the engineering bar for the team, design how coding agents carry out the ML lifecycle from data preparation to deployment, and grow production practice together with Data Scientists.

Requirements

• Have shipped and operated ML systems in production for 3+ years and know the common failure points: training/serving skew, leakage, drift and silent degradation.
• Be fluent in Python and SQL plus one more language such as Go or Java, and able to read, review and debug production code, whoever or whatever wrote it.
• Design clean contracts between data, models and consumers, and reason about latency, cost and failure.
• Understand forecasting, regression and optimization well enough to challenge a model design and recognize a wrong model in production.
• Define acceptance criteria, direct coding agents for implementation, QA and security, and step in when they fall short. Judge outcomes rather than individual steps, and want to shape how a team works this way.
• Use containers, orchestration, CI/CD and model registries daily, and have hands-on experience with a major cloud platform, ideally AWS.
• Infrastructure as code is a plus.
• Work as a partner to Data Science, Product and Engineering: challenge unclear problem framing, explain trade-offs in business terms, and communicate fluently in English across cultures.

Conditions

Based in Lisbon with two office days a week and flexible hours.

The workplace offers spaces for both focused work and team collaboration.

Benefits

• Work alongside international engineers, product experts and business teams in Lisbon's tech hubs.
• Regular events with internal and external speakers to keep learning, across teams and borders.
• 28 vacation days per year, an extra day off on your birthday and one volunteer day per year.
• Private health insurance that also covers your spouse and children free of charge.
• A yearly Coverflex allowance and a daily meal allowance.
• Exclusive rates on all company services, with special discounts extended to family and friends.