About the Role
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.
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 ML roadmap priorities across systems, experiments, and hiring, and guide the team's technical direction as it grows.
What We're Looking For
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.
Compensation & Benefits
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.