Data Intelligence MLOps Engineer
This MLOps role involves designing and industrializing AI models into production-grade pipelines. Responsibilities include building end-to-end orchestration, implementing ML CI/CD/CT systems, and ensuring model observability. The candidate must be proficient in Python, containerization, and modern orchestration tools. The role requires previous experience successfully shipping ML projects to high-availability environments.
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Experience
3+ years
Function
Engineering
Work mode
Onsite, United Arab Emirates
Company
Tier 3
What you will work on
This MLOps role involves designing and industrializing AI models into production-grade pipelines. Responsibilities include building end-to-end orchestration, implementing ML CI/CD/CT systems, and ensuring model observability. The candidate must be proficient in Python, containerization, and modern orchestration tools. The role requires previous experience successfully shipping ML projects to high-availability environments.
TAL's take
The role is posted through a third-party portal rather than the direct company, lowering reliability and caliber score.
The JD provides a very clear scope, specific responsibilities, and a defined technology stack.
Must haves
- 3+ years in DevOps, Data Engineering, or MLOps roles
- Experience taking an ML project to production
- Proficiency in Python and Bash
- Expertise in Kubeflow, Airflow, Dagster, or Prefect
- Mastery of Docker and Kubernetes
- Experience with cloud ML platforms (AWS/GCP/Azure)
Tools and skills
About the company
Talentmate acts as a job portal/recruitment platform rather than a direct engineering company for the Dyson role mentioned.
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