AI Threat Defense Engineer, Professional Services Organization
New
We sent a six-digit code to . Enter it below — or use the link in the same email.
Or click the link in the same email — either works.
Enter the email address on your account and we'll send you a link to set a new password.
Remembered it? Sign In
You'll own the ML function from day one at this early-stage AI startup, structuring training data pipelines, designing evals for agent systems, and building infrastructure for post-training and reasoning. The role requires 3+ years delivering production ML systems, with hands-on experience in post-training pipelines, agent environments, and RL training. You'll need strong Python and systems programming skills, expertise in evaluation frameworks and trajectory data, and experience with data validation and observability. Based primarily on-site in Munich with offices in Zurich and San Francisco, the position pays $100,000–$200,000 annually and does not offer visa sponsorship.
Written from this posting by Neural Jobs AI. The full description is below.
This is a founding ML engineering role at an early-stage AI startup, giving you full ownership of the ML function from day one. Working directly with founders and researchers, you will shape the technical direction of post-training pipelines and agent systems while building the team around you.
Structure, filter, and score experimental trajectories to build high-quality training data pipelines.
Design and implement evals and benchmarks that measure model reasoning, planning, and experimental improvement.
Build reliable agent environments, tool interfaces, observability systems, and replay infrastructure.
Establish robust validation and provenance tracking for trajectory and data quality.
Set ML roadmap priorities across systems, experiments, and hiring decisions.
Lead and grow the ML team's technical direction as the company scales.
3+ years of machine learning engineering experience delivering production ML systems.
Hands-on experience with post-training data pipelines, including structuring, filtering, and scoring training data.
Demonstrated experience building agent environments, tool interfaces, and RL training systems.
Strong Python and systems-level programming skills for ML infrastructure.
Experience designing and implementing evaluation frameworks and benchmarks for ML 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 the ability to bridge research and production seamlessly.
Background at a frontier AI lab or on a post-training or evals team is a strong plus.
Experience with reinforcement learning algorithm implementation, replay systems, or agent debugging tools is a plus.
Salary range: $100,000 to $200,000 USD annually. Visa sponsorship is not available.
On-site role based primarily in Munich, Germany, with additional offices in Zurich and San Francisco. Remote arrangements may be discussed on a case-by-case basis.
Here is what this employer asked for. Sign in and we will fill in your half.
Clera is an AI recruiting platform that introduces candidates directly to hiring managers at the companies they want to work for.
Search by role, company, or anything a posting mentions.
