Founding Machine Learning Engineer

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.

• 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.

• 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.

Salary range: USD 100,000 to 200,000 annually. Visa sponsorship is not available.

Location

On-site in Munich, Germany.