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
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Structure, filter, and score experimental trajectories for post-training data pipelines.
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Design and implement evaluations and benchmarks for model reasoning, planning, and experimental progress.
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Build reliable agent environments, tool interfaces, observability systems, and replay infrastructure.
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Establish validation and provenance tracking for trajectory and data quality.
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Set ML roadmap priorities across systems, experiments, and hiring, and lead the team's technical direction as it grows.
What We're Looking For
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At least 3 years of experience in machine learning engineering roles delivering production ML systems.
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Strong Python and systems-level programming skills, with production software engineering experience building ML infrastructure.
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Hands-on experience with post-training data pipelines, including structuring, filtering, and scoring training data.
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Experience designing and implementing evaluation frameworks and model benchmarks.
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Knowledge of trajectory data, reward modeling, agent decision-making, reinforcement learning, and agent environment design.
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Experience building replay and debugging tools, data validation and provenance systems, observability, tool interfaces, or RL training systems.
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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.
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