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Salary
$100k – $200k per year
Location
In office (Munich)
Seniority
Middle · 3+ years exp
Visa
No sponsorship (stated in the posting)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 9, 2026. First seen by Alion on Oct 8, 2026. Clera scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Clera is a San Francisco company that runs an AI recruiting platform positioned as a talent agent rather than a job board, matching engineers and other technical candidates to roles at venture-backed startups. Its system reads a candidate's background and preferences, then represents them to hiring teams at companies funded by firms such as Andreessen Horowitz, Y Combinator, Index Ventures and General Catalyst, compressing the introduction step that traditional headhunting handles manually. The model is aimed at the segment where recruiter fees are highest and candidate supply is thinnest, and the platform handles screening, scheduling and pipeline tracking for both sides of the match.

About the Role

As the founding machine learning engineer at an early-stage AI agent systems startup, 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 post-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 lead the team's technical direction as it grows.

What We're Looking For

  • At least 3 years of experience in machine learning engineering roles delivering production ML systems.

  • Strong Python and systems-level programming skills, with production software engineering experience building ML infrastructure.

  • Hands-on experience with post-training data pipelines, including structuring, filtering, and scoring training data.

  • Experience designing and implementing evaluation frameworks and model benchmarks.

  • Knowledge of trajectory data, reward modeling, agent decision-making, reinforcement learning, and agent environment design.

  • Experience building replay and debugging tools, data validation and provenance systems, observability, tool interfaces, or RL training systems.

  • Ability to connect research with production, take ownership, and work effectively in an ambiguous environment. Experience at a frontier AI lab or in post-training or evaluations at scale is a plus.

Compensation & Benefits

Salary range: USD 100,000 to 200,000 annually. Visa sponsorship is not available.

Location

On-site in Munich, Germany.

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