About the Role
As the founding machine learning engineer at an early-stage AI agent systems startup, you will build the ML function from the ground up. You will shape post-training and agent systems, set technical priorities, and help grow the team.
What You'll Do
Structure, filter, and score experimental trajectories for post-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, and lead the team's technical direction as it grows.
What We're Looking For
At least 3 years of experience in machine learning engineering roles delivering production ML systems.
Strong Python and systems-level programming skills, with production software engineering experience building ML infrastructure.
Hands-on experience with post-training data pipelines, including structuring, filtering, and scoring training data.
Experience designing and implementing evaluation frameworks and model benchmarks.
Knowledge of trajectory data, reward modeling, agent decision-making, reinforcement learning, and agent environment design.
Experience building replay and debugging tools, data validation and provenance systems, observability, tool interfaces, or RL training systems.
Ability to connect research with production, take ownership, and work effectively in an ambiguous environment. Experience at a frontier AI lab or in post-training or evaluations at scale is a plus.
Compensation & Benefits
Salary range: USD 100,000 to 200,000 annually. Visa sponsorship is not available.
Location
On-site in Munich, Germany.