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Personio is seeking a Staff AI/ML Engineer in Berlin to take technical ownership of AI/ML work end-to-end. You will lead projects from idea to implementation, shape how AI is built and scaled, and tackle complex problems with a strong product focus.
You will drive the design of AI systems, oversee production pipelines, and collaborate across teams to align AI initiatives with business goals. The role emphasizes hands-on leadership and deep technical decision-making.
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.
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.
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.