Founding Machine Learning Engineer

As the founding machine learning engineer at an early-stage AI company, 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 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 guide the team's technical direction as it grows.

• At least 3 years of machine learning engineering experience building or delivering production ML systems, with 3 to 8 years of overall relevant experience preferred.
• Strong Python and systems-level programming skills, with production software engineering experience.
• Hands-on experience with post-training ML, including data pipelines for structuring, filtering, and scoring training data.
• Experience designing and implementing model evaluation frameworks and benchmarks.
• Understanding of trajectories, reward structures, tool use, and agent environment design; experience with reinforcement learning algorithms and training systems is valuable.
• Experience building agent environments, replay and debugging tools, data validation, provenance tracking, or ML pipeline observability is a plus.
• Background in frontier AI research, scaled post-training or evaluation teams, or production agent systems is beneficial.

Annual salary range: $100,000 to $250,000 USD. Visa sponsorship is not available.

Location

On-site in Munich, Germany. Other listed locations include Zurich, Switzerland, and San Francisco, United States; remote arrangements may be discussed.