Senior MLOps Engineer (Contract)

turingedge Kuwait City Metropolitan Area
Remote
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AI Summary

We're hiring a Senior MLOps Engineer for a 7-month contract role. The ideal candidate has 10+ years of experience in building and managing production-grade ML infrastructure. Key responsibilities include designing and managing ML pipelines, implementing CI/CD processes, and ensuring reproducibility and governance across the ML lifecycle.

Key Highlights
7-month contract role
10+ years of experience in MLOps
Design and manage ML pipelines
Key Responsibilities
Design and manage ML pipelines for training, validation, deployment, and monitoring
Implement CI/CD processes for machine learning systems
Manage cloud and containerized environments for ML workloads
Technical Skills Required
MLflow Kubeflow Docker Kubernetes Azure ML AWS SageMaker GCP Vertex AI CI/CD Model versioning Monitoring
Benefits & Perks
Approx. USD 100/day
Accommodation provided by the client
Remote work
Nice to Have
Strong collaboration across ML, backend, cloud, and DevOps teams

Job Description


We’re Hiring: Senior MLOps Engineer (Contract Role – 7 Months)

We are looking for an experienced Senior MLOps Engineer to join a high-impact contract engagement.

This role is ideal for senior professionals who have hands-on experience in building and managing production-grade ML infrastructure, deployment pipelines, monitoring systems, and scalable MLOps workflows.

Experience Requirement
  • Minimum 10+ years of total corporate experience is mandatory
  • Stronger MLOps / ML platform / cloud infrastructure experience will be preferred
  • Extensive experience in production ML systems, CI/CD, orchestration, and lifecycle management is a major advantage
Key Responsibilities
  • Design and manage ML pipelines for training, validation, deployment, and monitoring
  • Build scalable automation workflows for ML operations
  • Implement CI/CD processes for machine learning systems
  • Manage cloud and containerized environments for ML workloads
  • Ensure reproducibility, governance, reliability, and observability across the ML lifecycle
Preferred Skills
  • MLflow, Kubeflow, Docker, Kubernetes
  • Azure ML / AWS SageMaker / GCP Vertex AI
  • CI/CD, model versioning, monitoring, and production optimization
  • Strong collaboration across ML, backend, cloud, and DevOps teams
Opportunity Details
  • Duration: 7 months
  • Compensation: Approx. USD 100/day
  • Accommodation: Provided by the client
  • The role is expected to start remotely due to the current war situation
  • Once conditions improve, relocation may be required based on client needs

If you are a senior MLOps professional with strong enterprise delivery experience, feel free to DM or share your profile.

  • #Hiring #MLOps #MLOpsEngineer #AIInfrastructure #MachineLearning #Kubernetes #Docker #MLflow #AzureML #AWS #GCP #ContractJobs #TechHiring

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