Join our team of machine learning experts to bring cutting-edge causal inference models and algorithms into production at scale. Collaborate closely with data scientists to deploy, optimize, and maintain models that drive performance marketing, portfolio optimization, and large-scale ad automation. You will build robust and scalable pipelines, ensuring these advanced solutions deliver actionable insights and measurable impact in real-world applications.
YOUR ROLE AT SIXT
Model Deployment and Optimization: Work with data scientists to implement and deploy causal inference models for online marketing optimization and automation —including A/B testing, difference-in-differences, propensity score matching, and double machine learning—in production environments.
Build and Maintain ML Pipelines: Design, develop, and maintain end-to-end pipelines for deploying machine learning models, ensuring scalability, reliability, and seamless integration with existing systems.
Cross-Functional Collaboration: Collaborate with data scientists, product managers, and software engineers to transform experimental models into fully operational systems that drive business outcomes.
Monitoring and Performance Tuning: Continuously monitor deployed models for performance, latency, and accuracy. Implement feedback loops and conduct regular updates to improve and adapt models to changing business needs.
Scalability and Automation: Automate repetitive tasks and build scalable infrastructure to handle large-scale data and high-throughput model serving.
Knowledge Sharing: Document best practices and deployment workflows. Communicate technical implementation details and insights to technical and non-technical stakeholders to foster collaboration and understanding.
YOUR SKILLS MATTER
Strong Foundations in Machine Learning Engineering: Experience in building, deploying, and maintaining ML models in production, with a focus on ensuring robustness and scalability.
Proficiency in Python and production-oriented ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
Experience with ML pipeline tools like MLflow, Airflow.
Strong understanding of REST APIs, microservices architecture, and containerization tools like Docker and Kubernetes.
Familiarity with causal inference models and techniques, including A/B testing, difference-in-differences, and propensity score matching, is a plus.
Cloud and Big Data Experience: Hands-on experience with cloud platforms (AWS) and their ML/AI services.
Knowledge of distributed systems and big data technologies, such as Spark, Dask, or Polars, as well as multi-processing techniques for efficient offline learning and batch processing.
Collaboration and Communication Skills: Ability to work closely with data scientists to understand modeling requirements and translate them into scalable engineering solutions. Clear communication of technical concepts to cross-functional teams.
Problem-Solving Mindset: Proactive and growth-oriented, with a passion for addressing real-world problems through advanced engineering solutions.
WHAT WE OFFER
About us:
We are a leading global mobility service provider with sales of €3.07 billion and around 9,000 employees worldwide. Our mobility platform ONE combines our products SIXT rent (car rental), SIXT share (car sharing), SIXT ride (cab, driver and chauffeur services), SIXT+ (car subscription) and gives our customers access to our fleet of 222,000 vehicles, the services of 1,500 cooperation partners and around 1.5 million drivers worldwide. Together with our franchise partners, we are present in more than 110 countries at 2,098 rental stations. At SIXT, a first-class customer experience and outstanding customer service are our top priorities. We focus on true entrepreneurship and long-term stability and align our corporate strategy with foresight. Want to take off with us and revolutionize the world of mobility? Apply now!
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