Senior MLOps Engineer (Digital Oilfield Systems)

Eice Technology

Employer Active

Posted 10 hrs ago

Experience

10 - 12 Years

Job Location

Kuwait - Kuwait

Education

Any Graduation

Nationality

Any Nationality

Gender

Not Mentioned

Vacancy

1 Vacancy

Job Description

Roles & Responsibilities

Key Responsibilities

  • Build and maintain end-to-end ML pipelines for data prep, training, validation, deployment, and monitoring.
  • Implement model governance: versioning, rollbacks, audit trails, and explainability.
  • Set up and manage containerized and scalable environments using Docker/Kubernetes.
  • Collaborate with software, IT, and data teams for model integration and compliance.
  • Enhance ML lifecycle workflows, automation, and best practices.
  • Monitor model performance, detect drift, and ensure high availability of ML services.

Required Skills & Experience:

  • 10+ years of overall experience with ML Ops/DevOps engineering background.
  • Hands-on experience with MLflow, Azure ML, Kubeflow, or similar tools.
  • Solid understanding of CI/CD pipelines and scripting for automation.
  • Experience deploying Python-based ML models to production environments.
  • Knowledge of model monitoring, drift detection, logging, and alerting frameworks.

Nice to Have:

  • Understanding of Digital Oilfield systems or OT/IT integration.
  • Experience with Azure cloud services (preferred).
  • Familiarity with real-time streaming platforms (Kafka, IoT).
  • Exposure to enterprise security, compliance, and data access practices.

Certifications:

  • Azure DevOps Engineer or Azure AI Engineer (preferred).
  • AWS DevOps Engineer (optional).

Desired Candidate Profile

Job Overview:

We are looking for a highly experienced Senior ML Ops Engineer to streamline and operationalize machine learning solutions across Digital Oilfield (DOF) platforms. This role will ensure models are production-ready, scalable, secure, and monitored effectively. You will work closely with cross-functional teams to automate workflows, deploy models, and maintain ML system reliability in a dynamic environment. Oil & Gas domain exposure is a plus but not mandatory.

Company Industry

Department / Functional Area

Keywords

  • Senior MLOps Engineer (Digital Oilfield Systems)

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