AI Engineer

Artificialy; Zürich; Vor Ort; CHF 110.000 - 150.000; Vollzeit

Benefits dieser Stelle

Full-time contract

Mentorship and continuous learning

Office in Zurich or Lugano

Zusammenfassung

Artificialy in Switzerland seeks an AI Engineer to take AI solutions from prototype to production for financial clients. You will build reliable, scalable ML/LLM systems and ensure deployment quality.

Work with AI scientists, software engineers and infra teams to integrate solutions in enterprise settings using Docker, Kubernetes and CI/CD. Based in Switzerland with on-site work in Zurich or Lugano.

Qualifikationen

• Master's degree in Computer Science, Engineering or equivalent.
• 3+ years of experience as AI Engineer or similar role.
• Experience deploying ML/LLM systems in production (serving, monitoring, cost/latency optimization).
• Strong programming skills (Python, SQL) and familiarity with Docker, Kubernetes, CI/CD.
• Familiarity with ML libraries (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with cloud platforms (AWS, Azure, or GCP).
• Proficiency in English.

Aufgaben

• Handle full path from prototype to production - fine-tuning, deployment, inference optimization, monitoring and continuous improvement of ML/LLM systems.
• Projects may involve LLM serving and inference stacks, cost/latency optimization, structured-output reliability, model monitoring pipelines, or productionizing solutions with AI scientists.
• Collaborate with AI scientists, software engineering, infrastructure and domain experts to integrate solutions in enterprise ecosystems using modern deployment tooling (Docker, Kubernetes, CI/CD).

Kenntnisse

Python

SQL

CI/CD

Docker

Kubernetes

ML deployment

Cloud platforms (AWS/Azure/GCP)

English proficiency

Ausbildung

Master's degree in Computer Science or Engineering

Tools

Docker

Kubernetes

CI/CD pipelines

TensorFlow

PyTorch

Scikit-learn

AWS/Azure/GCP

Jobbeschreibung

Artificialyis an AI company based in Switzerland, with offices in Lugano and Zurich. We design and deliver AI solutions that are impactful, transparent, and tailored to real-world industry needs.

Founded in 2020 by pioneers with over 40 years of combined experience in the field, our team brings together talented engineers, physicists, and mathematicians from across Europe. We are driven by curiosity, technical excellence, and a shared ambition to build AI systems that make a tangible difference.

AI Engineer, who will work with clients in the financial sector to bring AI solutions from prototype to production, with responsibilities spanning fine-tuning, deployment, inference optimization, monitoring, and continuous improvement. You will work in project teams alongside AI scientists, ensuring systems are reliable, scalable, and aligned with the high standards typical in banking.

Working Location

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.

About the Role

• 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)

Qualificationsand Skills:

• 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

Weoffer:

• Full-timepermanentcontract
• A stimulating scientific environment with an informal working atmosphere
• Mentorship and continuous learning and close relationship withcutting-edgeresearch teams