Senior MLOps Expert (AWS)

NorthBay Solutions; Dubai; On-site; AED 200,000 - 300,000; Full time

Job summary

A leading technology firm based in Dubai is looking for a Senior MLOps professional with 8–12+ years of experience. You will design and operate end-to-end MLOps pipelines, leading production deployments using AWS. The position requires strong skills in CI/CD, model monitoring, and mentoring. Candidates must be passionate about building scalable machine learning platforms and have expertise in cloud services. Relocation is required for candidates outside the UAE.

Qualifications

• 8–12+ years of experience in MLOps or related field.
• Strong expertise in AWS cloud services for ML.
• Proficiency in developing CI/CD pipelines for ML workflows.

Responsibilities

• Design & operate end-to-end MLOps pipelines.
• Lead production ML deployments using AWS-native services.
• Build CI/CD pipelines for ML workflows & infrastructure.
• Implement model monitoring and automated retraining.
• Ensure scalability, security & cost optimization on AWS.
• Mentor engineers and define MLOps best practices.

Skills

MLOps & ML: Model lifecycle, deployment, monitoring

AWS: SageMaker, S3, EC2, Lambda, ECR, ECS, EKS, IAM, CloudWatch

DevOps: Docker, Kubernetes, CI/CD (GitHub Actions / Jenkins / GitLab CI)

Strong Python, data pipelines, SQL & NoSQL

Job description

Experience: 8–12+ Years

Relocation Required for candidates outside the UAE

Are you a Senior MLOps professional passionate about building production-grade machine learning platforms on AWS? This is a high-impact onsite role in the UAE where you’ll lead end-to-end MLOps architecture and work closely with Data Science and Engineering teams.

What You’ll Do

• Design & operate end-to-end MLOps pipelines (data → deployment → monitoring)
• Lead production ML deployments using AWS-native services
• Build CI/CD pipelines for ML workflows & infrastructure
• Implement model monitoring, drift detection & automated retraining
• Ensure scalability, security & cost optimization on AWS
• Mentor engineers and define MLOps best practices

Key Skills

• MLOps & ML: Model lifecycle, deployment, monitoring (TensorFlow, PyTorch, Scikit-learn, MLflow)
• AWS (Mandatory): SageMaker, S3, EC2, Lambda, ECR, ECS, EKS, IAM, CloudWatch
• DevOps: Docker, Kubernetes (EKS), CI/CD (GitHub Actions / Jenkins / GitLab CI), Terraform / CloudFormation
• Programming: Strong Python, data pipelines, SQL & NoSQL