5 days ago
Munich, GermanyStaff+
Base Salary
$100k - $200k/yr
Responsibilities
- Own the ML function and technical direction from day one in partnership with the founders and researchers.
- Build pipelines to structure, filter, score, validate, and track the provenance of experimental trajectories and training data.
- Design and implement model evaluation frameworks and benchmarks for reasoning, planning, and experimental improvement.
- Build reliable agent environments, tool interfaces, observability systems, replay infrastructure, and agent debugging capabilities.
- Set ML roadmap priorities across systems, experiments, and hiring decisions.
- Lead and grow the ML team as the company scales.
Requirements
- At least 3 years of experience delivering production machine learning systems.
- Hands-on experience with post-training data pipelines, including structuring, filtering, and scoring training data.
- Experience building agent environments, tool interfaces, and reinforcement learning training systems.
- Strong Python and systems-level programming skills for ML infrastructure.
- Experience designing and implementing evaluation frameworks and benchmarks for machine learning models.
- Deep understanding of trajectory data, reward modeling, and agent decision-making systems.
- Experience building data validation, provenance tracking, and observability systems for ML pipelines.
- High agency, comfort with ambiguity, and ability to bridge research and production.
- Experience with reinforcement learning algorithm implementation, replay systems, or agent debugging tools is preferred.
- A background at a frontier AI lab or on a post-training or evaluation team is a strong plus.
Benefits
- Salary range of $100,000 to $200,000 USD annually.
- Primarily on-site in Munich, Germany, with additional offices in Zurich and San Francisco.
- Remote arrangements may be discussed on a case-by-case basis.
- Visa sponsorship is not available.