About the Role
An early-stage AI systems company is seeking a Founding Machine Learning Engineer to build its machine learning function and shape the technical direction of post-training and agent systems. You will work closely with the founding team and help set priorities for experiments, infrastructure, and future team growth.
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 to improve trajectory and data quality.
Set machine learning roadmap priorities across systems, experiments, and hiring.
Guide the technical direction of the machine learning team as it grows.
What We're Looking For
At least 3 years of experience in machine learning engineering, building or delivering production machine learning systems.
Production software engineering experience with Python and systems-level programming for machine learning infrastructure.
Hands-on experience with post-training machine learning, evaluation frameworks, and training data pipelines, including structuring, filtering, and scoring data.
Strong understanding of trajectory data, reward structures, tool use, and agent environment design.
Experience building agent environments, reinforcement learning systems, replay tools, or trajectory debugging infrastructure is valuable.
Ability to connect research with production, take ownership, and work effectively in an ambiguous environment.
Compensation & Benefits
Annual base salary: $100,000 to $250,000 USD. Visa sponsorship is not available.
Location
On-site in Munich, Germany.