Founding Machine Learning Engineer

About the Role

This is a founding ML role at an early-stage AI startup, working directly with founders and researchers to build post-training and agent systems from the ground up. You will own the ML function entirely, setting technical direction, defining experiments, and growing the team as the company scales. The work sits at the frontier of post-training, reinforcement learning, and autonomous agent development.

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 scales.

What We're Looking For

3+ years of hands-on machine learning engineering experience delivering production ML systems. Direct experience with post-training data pipelines, including structuring, filtering, and scoring training data. Demonstrated ability to build agent environments, tool interfaces, and RL training systems.

Strong Python skills and systems-level programming experience 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. High agency and comfort operating with significant autonomy in an early-stage environment. Background at a frontier AI lab or on a post-training, evals, or RL team is a strong plus.

Experience building replay systems and debugging tools for agent trajectories is a plus. Location On-site in Munich, Germany (primary), with additional office locations in Zurich, Switzerland and San Francisco, California. Remote arrangements may be discussed.

Visa sponsorship is not available.

ABOUT THE ROLE

This is a founding ML role at an early-stage AI startup, working directly with founders and researchers to build post-training and agent systems from the ground up. You will own the ML function entirely, setting technical direction, defining experiments, and growing the team as the company scales. The work sits at the frontier of post-training, reinforcement learning, and autonomous agent development.

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 scales.

WHAT WE'RE LOOKING FOR

- 3+ years of hands-on machine learning engineering experience delivering production ML systems.

• Direct experience with post-training data pipelines, including structuring, filtering, and scoring training data.
• Demonstrated ability to build agent environments, tool interfaces, and RL training systems.
• Strong Python skills and systems-level programming experience 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.
• High agency and comfort operating with significant autonomy in an early-stage environment.
• Background at a frontier AI lab or on a post-training, evals, or RL team is a strong plus.
• Experience building replay systems and debugging tools for agent trajectories is a plus. LOCATION On-site in Munich, Germany (primary), with additional office locations in Zurich, Switzerland and San Francisco, California. Remote arrangements may be discussed. Visa sponsorship is not available.