Function Description / Professional Tasks

We’re seeking a skilled MLOps Engineer to build and sustain a platform that turns data‑science ideas into production‑ready services. You’ll be the bridge between experimentation, deployment, and operations, ensuring models run reliably, securely, and cost‑effectively at scale.

What You Can Do:
− Design & evolve a reusable ML pipeline architecture that supports training, validation, and serving across teams.
− Automate model delivery pipelines, from code commit to production endpoint, leveraging continuous − integration / continuous deployment (CI/CD) practices with GitLab CI/CD and Kubernetes‑centric orchestration via ArgoCD for declarative application management.
− Collaborate with data scientists to translate prototypes into reproducible, production‑grade artifacts.
− Maintain a robust model lifecycle system: versioning, performance monitoring, drift detection, and rollback procedures.
− Optimize resource utilization and cost across the organization’s cloud footprint while meeting SLAs.
− Enforce data governance, privacy, and security standards throughout the ML platform stack.
− Build tooling for feature management, preprocessing, and evaluation that can be reused by multiple projects.
− Diagnose and resolve production incidents, working cross‑functionally to root‑cause and prevent recurrence.

Personal Skills and Education

What you bring: 
− Strong programming skills (Python preferred) with experience building end‑to‑end pipelines.
− Proven ability to containerize services and deploy them on Kubernetes clusters, using Helm for repeatable releases.
− Hands‑on experience configuring GitLab CI/CD pipelines that package code, tests, and model artifacts into automated build and deployment jobs.
− Familiarity with ArgoCD or equivalent GitOps tools for continuous delivery of applications to Kubernetes.
− Understanding of infrastructure‑as‑code concepts and cloud‑native deployment patterns.
− Experience implementing monitoring and alerting for model performance and operational health.
− Excellent problem‑solving, communication, and collaboration skills.

Nice to Have
− Hands‑on experience with feature stores or model registries that promote reuse and governance.
− Exposure to data versioning solutions that support reproducibility.
− Knowledge of MLOps frameworks (e.g., TFX, Kubeflow) and best‑practice patterns for Kubernetes deployments.
− Contributions to open‑source projects in the ML Ops ecosystem.

Education
− University/technical college degree in computer science or comparable.  

Language Skills
− English oral and written
− Optional: German oral (and written)

Additional Comments

− Willingness to travel
− Hybrid Model: One day a week @office (mandatory)

Why us?

Just by joining us you will get benefits like:

• Open minded company where every employee has to contribute to the development of the company - ideas are welcome as well as independent thinking too
• 25 annual days of vacations
• Flexible working hours
• Annual allowance for Benefits (Training, Gym, Public Transportation, Technologies, etc...)
• An amazing onboarding week at Switzerland
• iPhone
• Second Screen to work at home (Flat or a Curved one)
• First month Tech Allowance to buy your headset or, if you already have one, whatever you need to work comfortably
• Health insurance for you and your family
• Life insurance
• Office Perks (coffee, fruit, stand up desks. etc...)
• So much more...

About us

At the IT Campus, you can grow thanks to challenging IT projects, flat hierarchies, an inspiring environment and state-of-the-art technologies. You also have the opportunity to build up the IT Campus from scratch. You can work flexibly in terms of time and location and benefit from attractive working conditions.
Swiss Post connects people, brings cultures together and is one of the largest IT employers in Switzerland: We handle over 400 software projects each year and run more than 1,000 applications – with these figures set to rise in future.