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Salary
≈ $140k – $363k per year (Estimated)
Location
In office (Zurich)
Seniority
Senior · 2+ years exp
Visa
Sponsorship offered in the posting
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 20, 2026. First seen by Alion on Oct 15, 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 to turn experimental code into reliable, production-ready systems. You will build post-training pipelines for generating, processing, and evaluating research data, helping research ideas scale into repeatable experiments.

What You'll Do

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

  • Build distributed experiment support 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 preserving the integrity of experimental results.

  • Collaborate with researchers to turn ideas into robust, maintainable software.

What We're Looking For

  • Typically 2 to 10 or more years of relevant experience building machine learning training, inference, or data pipelines in Python.

  • 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 data processing at scale.

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

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

  • Experience with distributed tools such as PyTorch distributed, DeepSpeed, or Ray is helpful, as is familiarity with Transformers libraries, vLLM, or experiment tracking tools.

  • Background in reinforcement learning systems or working with video, audio, or image datasets is a plus.

Compensation & Benefits

Competitive compensation with equity is offered, along with health, dental, and vision coverage and professional development support. Visa sponsorship and relocation support are available.

Location

This is a full-time, on-site role in Zürich, Switzerland.

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