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MLOps Engineer

MLOps Engineer at Vurke Inc — Hatta, Dubai, United Arab Emirates. # MLOps Engineer **Job Title:** MLOps Engineer **Location:** Remote, UAE **Job Type:** Full-Time **Experience Required:** 4 to 7 years **Eligibility:** Male/Female...

Job Remote Full source details
Vurke Inc Source published Aug 18, 2026 Verified 2 weeks ago
✓ 100% verification score · Source: Vurke Inc Careers (Manatal) · Always confirm final requirements on the original source.
Complete source information imported The available role or programme description, requirements, benefits and source facts were imported from the public official endpoint and formatted for reading.
Employmentfull_time
Work modeRemote / location-flexible

Overview

MLOps Engineer at Vurke Inc — Hatta, Dubai, United Arab Emirates. # MLOps Engineer **Job Title:** MLOps Engineer **Location:** Remote, UAE **Job Type:** Full-Time **Experience Required:** 4 to 7 years **Eligibility:** Male/Female both can apply ## Role Description We are seeking an MLOps Engineer to support the deployment, monitoring, automation, and lifecycle management of machine learning systems in production environments. This role bridges machine learning and operations, ensuring that models move from experimentation to dependable real-world use.

Full job description

MLOps Engineer

Job Title: MLOps Engineer Location: Remote, UAE Job Type: Full-Time Experience Required: 4 to 7 years Eligibility: Male/Female both can apply

Role Description

We are seeking an MLOps Engineer to support the deployment, monitoring, automation, and lifecycle management of machine learning systems in production environments. This role bridges machine learning and operations, ensuring that models move from experimentation to dependable real-world use. You will work with data scientists, machine learning engineers, platform teams, and product stakeholders to improve reproducibility, model delivery, observability, and reliability. This role is ideal for someone who understands both ML workflows and operational discipline and can help build mature AI delivery practices.

Key Responsibilities

  • Support deployment and lifecycle management of ML systems
  • Build automation for training, validation, and release workflows
  • Improve monitoring and reliability of production models
  • Work with data and engineering teams on ML operations
  • Support infrastructure and environment consistency for ML workloads
  • Troubleshoot model delivery and runtime issues
  • Maintain operational documentation and standards

Required Skills

  • MLOps
  • Machine learning deployment
  • Automation
  • Monitoring
  • Environment management
  • Troubleshooting
  • Documentation
  • Collaboration

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