GenAI ML Engineer & MLOps — Production Pipelines

Sunrise GmbH; Zürich; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Zusammenfassung

Sunrise GmbH is building a production-grade ML/GenAI platform in a multinational environment. You design, build, deploy, and operate end-to-end ML solutions that deliver measurable business value while following governance and safety standards.

You will work within the central AI/ML Engineering & MLOps chapter, collaborating with Data Scientists and Domain Pods to deliver scalable, reusable platform components and best practices across the organization.

Qualifikationen

• 3+ years in ML engineering, MLOps or related roles with end-to-end production of ML/GenAI solutions.
• Hands-on CI/CD for ML workloads, IaC and GitOps.
• Experience with ML frameworks (scikit-learn, PyTorch, TensorFlow) and serving patterns (REST/gRPC).
• Strong Python software engineering, APIs, containers and cloud deployment patterns.

Aufgaben

• Translate business roadmaps into solution designs for ML/GenAI deployments.
• Industrialize prototypes with automated tests, secure packaging, deployment/rollback, and cost tuning.
• Build standardized CI/CD templates, model/prompt packaging, validation gates and dev→prod promotion.
• Operate model registry/versioning and automated retraining triggers aligned to governance.
• Provide reusable components and coach teams on MLOps/LLMOps best practices.

Kenntnisse

Python

CI/CD

MLOps

DevOps for ML

Communication

Ausbildung

Bachelor’s/Master’s in CS/Data Science or equivalent

Tools

Docker

Kubernetes

Terraform/Pulumi

MLflow

Kubeflow

Jobbeschreibung

Sunrise GmbH is building a production-grade ML/GenAI platform in a multinational environment. You design, build, deploy, and operate end-to-end ML solutions that deliver measurable business value while following governance and safety standards.

You will work within the central AI/ML Engineering & MLOps chapter, collaborating with Data Scientists and Domain Pods to deliver scalable, reusable platform components and best practices across the organization.