Stellendetails

ABOUT THE ROLE

Own the machine learning function at an early-stage AI company, working with founders and researchers to shape post-training and agent systems. You will set technical priorities and help guide the growth of the ML team.

WHAT YOU'LL DO

- Structure, filter, and score experimental trajectories for training data pipelines.

- Design and implement evaluations and benchmarks for model reasoning, planning, and experimental progress.

- Build reliable agent environments, tool interfaces, observability systems, and replay infrastructure.

- Establish validation and provenance tracking for trajectory and data quality.

- Set ML roadmap priorities across systems, experiments, and hiring.

- Lead the technical direction of the ML team as it grows.

WHAT WE'RE LOOKING FOR

- At least 3 years of professional machine learning engineering experience building or delivering production ML systems.

- Strong machine learning and software engineering skills, including production experience with Python and systems-level programming for ML infrastructure.

- Hands-on experience with post-training ML, including data pipelines for structuring, filtering, and scoring training data.

- Experience designing and implementing evaluation frameworks and benchmarks for ML models.

- Knowledge of trajectories, reward structures, tool use, and agent environment design.

- Experience with reinforcement learning, agent environments, replay systems, debugging tools, data validation, provenance, or ML pipeline observability.

- Background in frontier AI research or scaled post-training and evaluation teams is valuable.

- Comfort bridging research and production, taking ownership, and working in an ambiguous environment.

COMPENSATION & BENEFITS

Salary range: $100,000 to $250,000 USD annually. Visa sponsorship is not available.

LOCATION

On-site in Munich, Germany. Other listed locations include Zurich, Switzerland, and San Francisco, California.