ABOUT THE ROLE Own the machine learning function at an early-stage AI company, shaping post-training and agent systems from research through production. You will help set technical priorities and build the foundations for the ML team as it grows. WHAT YOU'LL DO - Structure, filter, and score experimental trajectories for 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 priorities for ML systems, experiments, and hiring, and lead technical direction as the team scales.
WHAT WE'RE LOOKING FOR - At least 3 years of professional experience building or delivering production machine learning systems. - Hands-on experience with post-training ML, evaluation frameworks, and post-training data pipelines, including structuring, filtering, and scoring training data. - Strong Python and systems-level software engineering skills for ML infrastructure. - Experience with agents, reinforcement learning, trajectory data, reward structures, and agent environment design. - Experience building evaluation benchmarks, replay and debugging tools, data validation, provenance tracking, or observability systems. - Ability to bridge research and production, take ownership, and work effectively in an ambiguous, fast-moving environment.
COMPENSATION & BENEFITS Salary range: $100,000 to $250,000 USD annually. Visa sponsorship is not available. LOCATION On-site in Munich, Germany.
Job description provided by Clera.
View the original posting
