About the role
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.