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.