ML Ops Engineer – Digital Oilfield

2 weeks ago

Kuwait City, Al Asimah B&B Hotel Hannover-City Full time 100,000 - 120,000 per year

Job Brief:

We are looking for an experienced ML Ops Engineer with 10 years of experience in deploying and managing machine learning models within digital oilfield environments. This remote opportunity is with one of our esteemed clients, offering the chance to work on cutting-edge data infrastructure and automation systems that drive next-generation energy analytics.

Key Responsibilities:

  • Design and implement scalable ML pipelines for digital oilfield data processing and automation.
  • Develop and maintain CI/CD frameworks for model training, validation, and deployment.
  • Collaborate with data scientists and domain experts to ensure reliable, production-grade model operations.
  • Manage and monitor ML models using tools such as MLflow, Kubeflow, or Airflow.
  • Implement best practices for data versioning, containerization (Docker), and orchestration (Kubernetes).
  • Ensure compliance with data governance, security, and performance standards.
  • Drive automation and performance optimization across the entire ML lifecycle.

Required Qualification / Experience / Skills:

  • Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
  • Minimum 10 years of experience in ML Ops or data engineering, preferably within the oil & gas sector.
  • Expertise in Python, Linux, Docker, and Kubernetes.
  • Strong understanding of CI/CD tools (GitLab CI, Jenkins) and cloud environments (AWS, Azure).
  • Proven experience deploying ML models in production for real-time analytics.
  • Familiarity with time-series data, IoT systems, and SCADA integration.
  • Excellent communication, documentation, and troubleshooting skills.

Job Location: Remote

Type of Employment: Permanent / Full time

Salary: Negotiable (based on experience)

What you can expect from the employer:

  • Competitive compensation based on experience.
  • Exposure to digital transformation projects in the energy industry.
  • Remote work flexibility and supportive work environment.
  • Continuous learning and career advancement opportunities.

Job Types: Full-time, Permanent

Application Question(s):

  • Do you have experience in ML Ops frameworks and deployment pipelines?
  • Have you worked in digital oilfield or industrial automation environments?
  • Are you experienced with Docker, Kubernetes, and cloud-based ML systems?
  • Do you have 10 years of relevant experience in ML Ops or related fields?

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