Full-Time Machine Learning Engineer

Join our team of data science and machine learning experts to shape the next generation of intelligent pricing strategies. Our mission is to apply cutting-edge techniques—including reinforcement learning, multi-armed bandits, and Bayesian inference—to optimize dynamic pricing decisions. We build scalable models and systems that directly impact millions of customers, enabling more efficient revenue management processes and a superior user experience.

YOUR ROLE AT SIXT:

1. Develop and Enhance ML Solutions: Design, implement, and maintain production-grade machine learning systems, with a strong focus on bandit algorithms and reinforcement learning methods for dynamic pricing.
2. Cross-Functional Collaboration: Work closely with teams in data science, engineering, product management, and business operations to bring experimental models into a robust production environment.
3. Monitoring and Analysis: Continuously track model performance, visualize key metrics, and conduct deep-dive analyses to understand changes in system behavior and their impact on business outcomes.
4. Iterative Improvement: Collaborate with business stakeholders to identify inefficiencies in current processes and propose data-driven, ML-powered solutions to address them.
5. Knowledge Sharing: Communicate results, methodologies, and technical insights to audiences of varying technical backgrounds, ensuring that both business and technical teams understand the value of your work.

YOUR SKILLS MATTER:

Foundational Experience in ML: Some background in machine learning or data science. Prior exposure to reinforcement learning, multi-armed bandits, Bayesian methods, or dynamic pricing is a plus, but not required.

Technical Skills: Proficiency in Python and familiarity with modern ML frameworks (e.g., TensorFlow, PyTorch). Experience with cloud platforms (AWS, GCP, or Azure) is beneficial.

Production Mindset: Comfortable deploying and maintaining ML models in a production environment, ensuring reliability, scalability, and adaptability.

Growth-Oriented: Passionate about learning new methods and solving real-world problems. Even if you don’t have all the experience listed, we encourage you to apply if you’re excited about bandit algorithms, dynamic pricing, and advanced ML techniques.

Communication & Teamwork: Fluent in English and enthusiastic about working within a diverse, multinational team.

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