Machine Learning Operations (MLOps) Specialist

leading-edge; Dubai; On-site; AED 300,000 - 520,000; Full time

Job summary

leading-edge is seeking an experienced MLOps Specialist in Dubai to bridge data science and IT operations, ensuring machine learning models move smoothly into production. You will design and maintain CI/CD pipelines, automate deployment, and implement IaC practices.

The role requires 5+ years in MLOps or DevOps, strong ML concepts, cloud experience (AWS/Azure/GCP), Python scripting, and proficiency with Docker and Kubernetes.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 5+ years in MLOps, DevOps, or a related role.
• Strong understanding of machine learning concepts, algorithms, and cloud platforms (AWS, Azure, GCP).
• Proficiency in Python or similar scripting languages.
• Experience with Docker and Kubernetes.
• Familiarity with Jenkins, GitLab CI, CircleCI, or similar CI/CD tools.

Responsibilities

• Developing and Maintaining CI/CD Pipelines: Create automated workflows for building, testing, and deploying machine learning models.
• Automating Deployment and Monitoring: Ensure models are deployed efficiently and their performance is continuously tracked in production environments.
• Implementing Infrastructure as Code (IaC): Manage ML infrastructure using code to ensure consistency and scalability.
• Troubleshooting and Resolving Issues: Identify and fix problems related to model deployment and performance.
• Collaboration: Work with data scientists and engineers to optimize model performance, scalability, and integration.

Skills

CI/CD pipelines

Automation & monitoring

IaC (Infrastructure as Code)

Troubleshooting

Collaboration

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes

Jenkins

GitLab CI

CircleCI

Job description

Job Summary:
A Machine Learning Operations (MLOps) Specialist plays a vital role in bridging the gap between data science and IT operations, ensuring seamless integration of machine learning models into production environments. Here’s a breakdown of the job:

Key Responsibilities:

• - Developing and Maintaining CI/CD Pipelines: Create automated workflows for building, testing, and deploying machine learning models.
• - Automating Deployment and Monitoring: Ensure models are deployed efficiently and their performance is continuously tracked in production environments.
• - Implementing Infrastructure as Code (IaC): Manage ML infrastructure using code to ensure consistency and scalability.
• - Troubleshooting and Resolving Issues: Identify and fix problems related to model deployment and performance.
• - Collaboration: Work with data scientists and engineers to optimize model performance, scalability, and integration.

Requirements:

• - Education: Bachelor’s degree in Computer Science, Engineering, or a related field.
• - Experience: 5+ years in MLOps, DevOps, or a related role.
• - Technical Expertise: Strong understanding of machine learning concepts, algorithms, and cloud platforms (AWS, Azure, GCP).
• - Scripting Skills: Proficiency in Python or similar scripting languages.
• - Containerization: Experience with Docker and Kubernetes.
• - CI/CD Tools: Familiarity with Jenkins, GitLab CI, CircleCI, or similar.