Senior AI/ML Engineer

ti&m AG

Zürich

Key information

Job summary

Join our innovative team working on AI/ML projects. Enjoy a dynamic environment with creative workshops and hands-on solutions.

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What to expect

Exciting and innovative projects for our clients. Depending on the need, we accompany the process with creative workshops, develop proof-of-concepts, and implement the solutions together.
We utilize a wide range of AI/ML technologies – from classic supervised learning to exploratory GenAI approaches like Agentic AI or the Model Context Protocol (MCP). Depending on the need, we work with RAG architectures, primarily in the Azure Cloud, but also in other environments or with open-weights models.
Our solutions are built on the Python ecosystem – from machine learning frameworks like PyTorch or scikit-learn to GenAI toolkits like LangChain or LlamaIndex, and backend frameworks like FastAPI. We realize MLOps and deployment with Terraform, Docker, Kubernetes, MLflow, and Azure ML.
A wide range of tasks – from initial workshops with clients (our "AI Kickstart" format) to data exploration and the implementation of scalable AI/ML solutions.
Continuous learning and ongoing training in the field of AI/ML, as well as insights into the various industries of our clients.
Variety and exciting collaboration in internal project teams as well as on-site with our clients.
An experienced and intrinsically motivated team of AI/ML and software engineers.

What you bring

Several years of experience (at least 5 years) in developing AI/ML applications – ideally in productive use for clients or own products.
A completed master's degree in computer science, data science, or a related field.
Very good knowledge of Python and relevant AI/ML frameworks (e.g., PyTorch, scikit-learn) as well as experience with modern backend stacks (e.g., FastAPI).
Optional: Experience with Java, Spring, or modern frontend technologies.
Experience with cloud services, especially regarding ML/AI services (preferably on Azure).
Practical experience in building AI architectures – from classic ML pipelines to complex GenAI solutions like RAG, Agentic workflows, or the Model Context Protocol (MCP).
You are familiar with embeddings, transformer architectures, and prompt engineering.
Strong software engineering skills: Ability to write clean, maintainable code – clean code is a given for you.
Experience with MLOps, deployment, and infrastructure – e.g., Docker, Kubernetes, Terraform, MLflow, Azure ML.
Experience working with CI/CD pipelines and GitOps workflows.
Proficient in working with relational databases (SQL) and common storage solutions.

We are looking for you – become part of our team