AI Engineer | Zurich | Switzerland

Job Location Zurich Switzerland

Experience (Years): 6 years

Pay Rate TBN

Start Date - ASAP

6 Months Contract Renewable

We are seeking an AI Engineer to collaborate with cross-functional teams in solving compliance and regulatory business challenges through innovative AI-powered solutions. You will contribute across the full lifecycle of AI model developmentfrom problem definition to deploymentensuring high-performance scalable and ethically responsible AI solutions.

In this role you will work on model development training fine-tuning prompt engineering and continuous improvement based on real-world performance and stakeholder feedback. You will design build test and integrate AI-powered applications while adhering to best software engineering practices. Effective communication with both technical and non-technical stakeholders is essential to align project goals and deliverables.

Responsibilities

• Collaborate with cross-functional teams to address compliance and regulatory business problems using AI-driven solutions.
  
• Contribute to the entire AI model lifecycle including problem definition development training fine-tuning deployment and ongoing improvements.
  
• Develop test and integrate AI-powered applications with strong adherence to software engineering best practices.
  
• Implement and refine RAG-based generative AI solutions and prompts.
  
• Continuously evaluate and improve model performance using real-world feedback.
  
• Communicate effectively with stakeholders across technical and business domains.
  

Requirements

• 35 years of experience in software engineering or a related role with exposure to AI/ML concepts and applications.
  
• Strong proficiency in Python for production-level software -on experience in application development including building and deploying APIs.
  
• Familiarity with AI/ML frameworks such as TensorFlow PyTorch Hugging Face and OpenAI API and their integration into applications.
  
• Experience with RAG-based generative AI solutions and strong knowledge of prompt engineering.
  
• Understanding of machine learning concepts including model types training fine-tuning and deployment.
  
• Knowledge of MLOps best practices (model lifecycle management monitoring scalability) is a plus.
  
• Experience with source control DevOps and CI/CD pipelines (Git Docker Kubernetes).
  
• Strong understanding of software engineering principles including scalability performance optimization and maintainability.
  
• A collaborative team player with a proactive approach to problem-solving and adaptability to new technologies.
  
• Degree in Computer Science Software Engineering Data Science or a related field (or equivalent experience).
  
  

Competencies

• Digital: Python
  
• Digital: Machine Learning
  
• Digital: Artificial Intelligence (AI)