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FREELANCE*
Cloud (ML)Ops Engineer
Contract details
Duration:
ASAP until end of year, with extensions
Language:
Fluency in English
Work setup:
50% onsite / 50% remote
Process: 1 Stage Interview
For a
banking client
, we are looking for a
Cloud (ML)Ops Engineer
to work at the intersection of cloud infrastructure, DevOps, and machine learning operations. You will help build and maintain a scalable, secure, and reliable platform supporting data scientists and analysts across their full workflow.
Key responsibilities
Design and build cloud-native platform services for AI models and data pipelines
Support multi-user Jupyter environments and cloud IDEs
Enable training, storage, serving, and monitoring of custom models (mainly high-throughput batch processing)
Expose models via APIs for low-latency use cases
Support Generative AI initiatives
Manage infrastructure on AWS using Terraform, Docker, and Kubernetes
Automate data and model lifecycle workflows (Airflow, Spark, Python)
Ensure platform reliability, performance, and cost efficiency
Support onboarding, troubleshooting, and continuous improvement of MLOps practices
Collaborate with stakeholders across multiple locations and countries
Requirements
Strong interest in cloud, data, and AI
Master’s degree in ICT, Engineering Sciences, Business Engineering (informatics focus), or equivalent experience
Strong Python skills and familiarity with the data science ecosystem
Experience with AWS cloud infrastructure
Docker \& Kubernetes knowledge
Infrastructure as Code (Terraform)
CI/CD experience (e.g. Jenkins, GitHub Actions)
Experience with big data tools such as Spark