About the role
ABOUT THE ROLE
As the founding machine learning engineer at an early-stage AI company, you will build the ML function from the ground up. You will shape post-training and agent systems, connecting research with reliable production infrastructure.
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 to support trajectory and data quality.
- Set priorities for the ML roadmap, experiments, systems, and hiring.
- Guide 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.
- Professional experience in post-training or model evaluations, including hands-on work structuring, filtering, and scoring training data.
- Production software engineering experience with Python and systems-level programming for ML infrastructure.
- Experience designing and implementing ML evaluation frameworks and benchmarks.
- Strong knowledge of trajectory data, reward structures, tool use, and agent decision-making.
- Experience building agent environments, replay and debugging tools, RL training systems, or data validation and observability infrastructure.
- Reinforcement learning implementation and tuning experience is valuable, as is experience in frontier AI research or scaled post-training and evaluation teams.
- Comfort owning priorities and working across research and production in an ambiguous environment.
COMPENSATION & BENEFITS
Base salary: $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; remote arrangements may be discussed.