Founding Machine Learning Engineer

This is a founding ML engineering role at an early-stage AI startup, where you will own the machine learning function from day one. Working closely with founders and researchers, you will shape the technical direction of post-training pipelines, agent systems, and the broader ML roadmap as the team scales. What You’ll Do Structure, filter, and score experimental trajectories for training data pipelines. Design and implement evals and benchmarks that measure model reasoning, planning, and experimental improvement. Build reliable agent environments, tool interfaces, observability systems, and replay infrastructure. Establish robust validation and provenance tracking for trajectory and data quality. Set ML roadmap priorities across systems, experiments, and hiring decisions. Lead the technical direction of the ML team as it grows., On-site in Munich, Germany (primary location), with additional offices in Zurich, Switzerland and San Francisco, California. Remote arrangements may be discussed on a case-by-case basis.

3 or more years in machine learning engineering roles with a track record of delivering production ML systems. Hands-on experience with post-training data pipelines, including structuring, filtering, and scoring training data. Demonstrated experience building agent environments, tool interfaces, and RL training systems. Production software engineering proficiency in Python and systems-level programming for ML infrastructure. Experience designing and implementing evaluation frameworks and benchmarks for ML models. Deep understanding of trajectory data, reward modeling, and agent decision-making systems. Experience building data validation, provenance tracking, and observability systems for ML pipelines. Background at a frontier AI lab or on a post-training or evals team at scale is a strong plus. High agency, comfort with ambiguity, and the ability to bridge research and production seamlessly.