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# AI Engineer

- **Company:** Blueprint School Network, Inc.
- **Location:** Zurich, KS, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Computer Programming, Continuous Integration, Distributed Data Store, Python (Programming Language), Tensorflow, Software Engineering, SQL Databases, Pytorch, Large Language Models, Scikit Learn, Kubernetes, Information Technology, Docker, Databricks
- **Published:** September 4, 2026
- **Apply:** https://artificialy.applytojob.com/apply/TAfs0WG3gS/AI-Engineer?source=GS

## About the Role

The role can be based in Zurich or Lugano. You must be willing to work onsite at least 80% of the time. Candidates must be based in Switzerland or willing to relocate to Switzerland., * Master's degree in Computer Science, Engineering, or equivalent.

 * 3+ years of working experience as AI Engineer or in a similar role
 * Experience deploying and operating ML/LLM systems in production (serving, monitoring, cost/latency optimization).
 * Strong programming skills (Python, SQL) and familiarity with deployment tooling (Docker, Kubernetes, CI/CD).
 * Familiarity with ML libraries (TensorFlow, PyTorch, Scikit-learn, etc.).
 * Hands-on experience with cloud platforms (AWS, Azure, or GCP).
 * Proficiency in English.

Nice to Have:

 * Experience with LLM inference stacks (e.g., vLLM) and structured-output reliability.
 * Familiarity with Databricks or distributed data frameworks.
 * Experience in finance or other regulated industries.

## Description

* Your responsibilities will span the full path from prototype to production - fine-tuning, deployment, inference optimization, monitoring, and continuous improvement of ML and LLM systems.
 * Projects may involve LLM serving and inference stacks, cost/latency optimization, structured-output reliability, model monitoring pipelines, or productionizing solutions designed alongside AI scientists.
 * You will work in project teams alongside AI scientists, software engineering, infrastructure, and domain experts to integrate solutions smoothly into enterprise ecosystems using modern deployment tooling (Docker, Kubernetes, CI/CD).


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