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Take AI into production: you build LLM and RAG applications, AI agents and ML pipelines that Swiss companies use every day.

Why this role matters

There are enough prototypes. What our clients lack are AI solutions that run securely, measurably and maintainably in production – in banks, insurers, healthcare and the public sector. Automation & AI is one of our focus areas, and you are the person who turns a use case into a system: with a clean data foundation, robust evaluation, monitoring and clear governance.

Your mission

You take machine learning and GenAI solutions from the first experiment into productive operation – and make sure they stay there: traceable, compliant with data protection and with measurable benefit for the business.

What you will do

• Build LLM and RAG applications: retrieval pipelines, chunking and embedding strategies, prompting and tool use for assistants, knowledge search and document processing
• Develop AI agents: agentic workflows that automate processes and are cleanly integrated into existing systems and APIs
• Make quality measurable: set up evaluation frameworks with test sets, metrics and LLM-as-a-judge, catch hallucinations and regressions early
• Run MLOps: training and deployment pipelines, monitoring, model and prompt versioning as well as CI/CD for ML workloads
• Prepare data: open up, clean and prepare data sources – with an eye on quality, provenance and access rights
• Use cloud platforms: implement solutions on Azure ML / Azure AI Foundry, Google Vertex AI or AWS SageMaker / Bedrock with good architecture and cost awareness
• Develop responsibly: account for data protection under the revised Swiss FADP, the requirements of the EU AI Act and responsible AI principles from the start
• Advise and enable: assess use cases with clients, judge feasibility and help teams get better at working with AI

Your profile

Must have

• Several years of experience as an ML engineer, a data scientist with an engineering focus or a software engineer with an ML focus
• Very good Python skills and experience with the common ML and GenAI ecosystem
• Hands-on experience with LLM applications and RAG in production, not only in a notebook
• Experience with at least one cloud ML platform (Azure, Google Cloud or AWS)
• An understanding of MLOps: pipelines, versioning, monitoring and deployment
• Awareness of data protection, security and the limits of AI systems
• Very good German and good English

Nice to have

• Experience with AI agents, function calling or orchestration frameworks
• Knowledge of vector databases, search systems and LLM evaluation
• Containers, Kubernetes and infrastructure as code
• Experience in regulated industries and with the EU AI Act

What you can expect

• Modern stacks & AI in daily work – you work with current models and platforms, not with legacy
• Your voice counts – we make decisions together and close to the work
• A direct line instead of hierarchy – from idea to decision without detours
• Real responsibility from day one – you shape the architecture and approach of your projects
• You shape how we work – you actively develop our own AI offering further
• Training & certifications – targeted on Azure, Google Cloud and AWS
• Demanding projects in banking, insurance, healthcare, telecommunications and the public sector

How we work

Hybrid across Switzerland, with our office in Meggen near Lucerne. Remote where it fits, at the client where it helps the collaboration. 80–100 %, starting by agreement.

Applying

Send us your CV or a short profile to hello@gridz.ch. A link to GitHub, a project or a paper you are proud of often tells us more than a cover letter.

What does the process look like?
An introductory conversation, then a technical discussion about a real use case – no coding marathon.

Apply now