MLOps Engineer

Are you passionate about

cloud infrastructure, DevOps, and machine learning

? As a Cloud (ML)Ops Engineer, you’ll help build a

reliable, scalable, and secure platform

that empowers data scientists and analysts to bring AI ideas to life.

What you’ll do:

✨ Host a

multi-user Jupyter environment

and a cloud IDE

✨ Build frameworks for

training, storing, serving, and monitoring models

✨ Expose models via

APIs

for low-latency applications

✨ Enable

Generative AI initiatives

across the organization

Your mission includes:

Designing and building

cloud-native services

for AI models and data pipelines

Collaborating with colleagues across countries to deliver

cutting-edge solutions

Managing infrastructure with

Terraform, Docker, and Kubernetes on AWS

Automating workflows for

data processing and model lifecycle management

(Airflow, Spark, Python)

Ensuring

platform reliability, performance, and cost-efficiency

Supporting colleagues in platform usage, including onboarding and troubleshooting

Driving the evolution of

MLOps practices

What we’re looking for:

You’re curious about cloud, data, and AI, and excited to learn and innovate.

Education \& Experience:

🎓 Master’s degree in ICT, Engineering, Business Engineering with Informatics focus, or equivalent experience

Technical Skills:

Strong

Python

skills and familiarity with the data science ecosystem

Experience with

cloud infrastructure

(AWS preferred)

Proficiency with

Docker \& Kubernetes

Skilled in

Infrastructure as Code (Terraform)

Experience with

CI/CD tools

(Jenkins, GitHub Actions)

Knowledge of

big data tools

such as Spark

If you’re ready to

take AI to the next level

and work in a dynamic, innovative environment, this is your chance! 💡