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Salary
≈ $124k – $279k per year (Estimated)
Location
In office (Zurich)
Visa
Sponsorship offered in the posting
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 4, 2026. First seen by Alion on Oct 3, 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

Join an AI research team as a Research Engineer, turning experimental code into production-ready systems. You will build the shared infrastructure and post-training pipelines that help research projects scale while preserving experimental integrity.

What You'll Do

  • Turn research prototypes into tested, reusable data generation, training, and evaluation pipelines.

  • Build distributed experiment infrastructure for data loading, checkpointing, and collecting agent interactions.

  • Profile workloads and improve GPU utilization, memory efficiency, and data throughput.

  • Develop tests, experiment tracking, and debugging tools while ensuring changes preserve research results.

  • Work with researchers to translate ideas into robust, maintainable software.

What We're Looking For

  • Strong Python skills and hands-on experience with PyTorch, JAX, or a comparable machine learning framework.

  • Experience building and debugging software for model training, inference, or large-scale data processing.

  • Understanding of machine learning experiments and how data, numerical precision, and implementation choices affect results.

  • Sound software engineering practices, including testing, profiling, version control, and documentation.

  • Distributed training or data processing experience with tools such as PyTorch distributed, DeepSpeed, or Ray is valuable.

  • Familiarity with model-serving, machine learning, or experiment tracking tools is a plus; reinforcement learning systems and multimodal datasets are also useful.

Compensation & Benefits

Equity is provided. Visa sponsorship is available.

Location

On-site in Zurich, Switzerland. San Francisco, California is also listed as a work location.

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