Staff Machine Learning Engineer
Set technical direction for production AI agents and model training, evaluation, and MLOps while remaining hands-on. Shape the ML roadmap and improve systems that handle sensitive healthcare data.
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You want to help build the central MLOps/LLMOps Platform that supports over 80 Data Scientists and ML Engineers worldwide? Then join our Data Science team and design and build scalable solutions for classical ML use cases and next-generation LLMOps workloads, directly influencing the experience of millions of customers and advancing SIXTβs AI capabilities. If you are passionate about innovative AI platforms and want to make an impact, apply now and become part of Team Orange in Pullach close to Munich.
YOURS TO OWN
YOUR SKILLS MATTER
WHAT WE OFFER
About us:
We are a globally leading mobility service provider with a revenue of β¬4.3 billion and around 9,000 employees worldwide. Our mobility platform ONE combines our products SIXT rent (car rental), SIXT share (car sharing), SIXT ride (taxi, ride, and chauffeur services), and SIXT+ (car subscription), giving our customers access to our fleet of 360,000 vehicles, the services of 4,000 cooperation partners, and around 5 million drivers worldwide. Together with our franchise partners, we are present in more than 100 countries at 2,000 rental stations. At SIXT, top-tier customer experience and outstanding customer service are our highest priorities. We believe in true entrepreneurship and long-term stability and align our corporate strategy with foresight. Get started with us and apply now!
Set technical direction for production AI agents and model training, evaluation, and MLOps while remaining hands-on. Shape the ML roadmap and improve systems that handle sensitive healthcare data.
Lead the technical direction of production machine learning systems for deposition and meeting products, building grounded LLM pipelines and evaluations while guiding architecture, reliability, and engineering practices.
Lead the development and deployment of production machine-learning systems for manufacturing and MRO, turning sparse industrial data and simulation into validated, transferable tools with measurable shop-floor impact.
Own cross-team machine learning architecture and evaluation standards, guide agentic AI design, and strengthen production practices across AI teams while ensuring safe, compliant deployment.
Develop and evaluate machine-learning methods that help autonomous-driving models transfer reliably across vehicle platforms, diagnosing real-world failures and improving production performance.