Founding Machine Learning Engineer

About the Role

This is a founding ML engineering role at an early-stage AI startup, giving you full ownership of the ML function from day one. Working directly with founders and researchers, you will shape the technical direction of post-training pipelines and agent systems while building the team around you.

What You'll Do

• Structure, filter, and score experimental trajectories to build high-quality 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 and grow the ML team's technical direction as the company scales.

What We're Looking For

• 3+ years of machine learning engineering experience 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.

• Strong Python and systems-level programming skills 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, comfort with ambiguity, and the ability to bridge research and production seamlessly.

• Background at a frontier AI lab or on a post-training or evals team is a strong plus.

• Experience with reinforcement learning algorithm implementation, replay systems, or agent debugging tools is a plus.

Compensation & Benefits

Salary range: $100,000 to $200,000 USD annually. Visa sponsorship is not available.

Location

On-site role based primarily in Munich, Germany, with additional offices in Zurich and San Francisco. Remote arrangements may be discussed on a case-by-case basis.