ML Engineer Reinforcement Multi-Armed Bandits - Hybrid Lisbon

ML Engineer Reinforcement Multi-Armed Bandits - Hybrid Lisbon Join an innovative, global mobility-tech leader in Lisbon as an ML Engineer specialising in Reinforcement Learning and Multi-Armed Bandit algorithms. In this hybrid role, you’ll develop and deploy advanced ML systems powering millions of dynamic decisions daily. Collaborate with cross-functional teams in a vibrant, diverse environment that values curiosity, experimentation, and real-world impact. Key Responsibilities – Machine Learning Engineer (Reinforcement Learning & Multi-Armed Bandits), Lisbon Design, prototype, and optimise multi-armed bandit models with contextual inputs and enhanced uncertainty quantification Implement, scale, and productionise reinforcement learning pipelines for real-time pricing, recommendation, or allocation systems Drive the full ML lifecycle: from feature engineering and data preprocessing through model validation, packaging, and deployment Utilise scalable inference techniques (e.g., SVI, MCMC, variational inference) on large, high-volume datasets Develop robust, reproducible ML workflows in Python using tools such as PyMC, TensorFlow Probability, or NumPyro Integrate models seamlessly into cloud-based and containerised production environments (using Docker, Kubernetes, and workflow schedulers such as Airflow or Dagster) Continuously monitor model performance and detect anomalies or data drift with Bayesian control charts and real-time dashboards Partner with product, analytics, and engineering stakeholders to translate business needs into measurable ML solutions Share knowledge by mentoring others, running workshops, and contributing to technical documentation/publications Skills and Qualifications – Reinforcement Learning & Bandit Algorithms, Lisbon Hybrid 5+ years hands-on experience applying statistical and machine learning models in production, including reinforcement learning or online decision-making systems Practical expertise building, extending, and deploying multi-armed bandit models (contextual, Bayesian, or hierarchical variants preferred) Advanced working knowledge of Python and ML libraries: PyMC, Stan, NumPyro, TensorFlow Probability, or similar Demonstrated proficiency with scalable inference approaches: SVI, MCMC, black-box VI, or related methods Experience developing cloud-native and containerised ML solutions (AWS, GCP, or Azure; Docker and Kubernetes) Comfort with CI/CD, automated testing, and modern software engineering practices Excellent communication skills; adept at collaborating cross-functionally and articulating technical concepts to varied audiences Curious, proactive, and eager to stay up to date with the latest advances in probabilistic machine learning Fluent English required; eligibility to work in Portugal and regular on-site attendance in Lisbon as part of a hybrid model Benefits & Offer – ML Engineering Careers in Lisbon Comprehensive package: 28 days holiday, birthday leave, and volunteer days Private health insurance to support your wellbeing Flexible, hybrid work structure with no dress code Coverflex platform, transport and travel discounts, plus additional perks Continuous professional growth: funding for conferences, training, and tailored career development Inclusive, supportive team environment that celebrates talent from all backgrounds Who Succeeds in This Role? This opportunity is perfect for a knowledgeable, creative problem-solver who thrives at the interface of reinforcement learning, bandit algorithms, and real-time data systems. If you value autonomy, impact, and continuous learning—and wish to help shape the future of mobility technology—this Lisbon-based hybrid role is your next step. How to Apply – Machine Learning Engineering Jobs (Reinforcement Learning & Bandit Focus), Lisbon Ready to advance your ML career at the forefront of industry innovation? Submit your CV in English today. We encourage applications from candidates of all genders, backgrounds, and identities – help us build a forward-thinking, inclusive team in Lisbon! Locations Lisbon Portugal Remote status Hybrid