Staff AI/ML Engineer (all) in Großmehring, München

Who we are looking for We’re looking for a Staff AI/ML Engineer to take technical ownership of our AI/ML work end-to-end. You’ll work on complex AI/ML problems, lead projects from idea to implementation, and help shape how we build and scale AI across the company. You’ll bring hands-on experience building and leading projects end-to-end, along with the ability to go deep into technical decisions, edge cases, and trade-offs. Your mission Solve complex problems using the right AI/ML approach, from classic ML to GenAI and LLMs, depending on the problem. Design AI/ML systems and architecture, including greenfield projects. Evaluate, monitor, and maintain AI/ML pipelines in production— not only build AI/ML solutions, but also assess their performance and keep them reliable over time. Audit our current AI setupand help define the AI strategy and roadmap. Lead cross-functional AI initiativesand drive them from idea to implementation. Challenge existing technical decisions constructivelyand stay focused on the product and the result. Your background Proven experienceleading AI/ML projects end-to-end in a startup/product environment. StrongAI/ML and Data Science expertise, includingclassic ML and GenAI, with a solidsoftware engineering foundationand hands-on experience building AI/ML solutions. Understanding ofdata and ML infrastructure, includingdata quality, feature/data pipelines, model serving, observability, deployment, and lifecycle management. Strongsystem design and architectureskills. Proactive, ownership-driven, and results-oriented, with a strongproduct mindset. Open to feedback and comfortablechallenging technical decisions constructively. Why us? Top Tech company in Digital Health: Work in a fast-growing, innovative environment where your impact is visible. True impact in healthcare: Contribute to a unique platform with the potential to improve health for millions. International team: Join colleagues from 14+ nationalities, united by a shared vision. Hiring Process Recruiter Screening Leadership Interview Technical Deep Dive Decision #J-18808-Ljbffr