Machine Learning Operations Specialist

Leading Edge; Dubai; On-site; AED 293,000 - 441,000; Full time

Job summary

A technology solutions firm in Dubai is seeking an experienced Machine Learning Operations (MLOps) Specialist to integrate machine learning models into production environments. You will develop CI/CD pipelines, automate deployment, and ensure model performance tracking. The ideal candidate holds a Bachelor's degree in Computer Science with 5+ years of experience in MLOps and is proficient in Python. Experience with cloud platforms like AWS, Azure, or GCP is essential. This role offers a dynamic work environment in a growing firm.

Qualifications

• Bachelor's degree in Computer Science, Engineering or a related field.
• 5 years of experience in MLOps, DevOps or a related role.
• Strong understanding of machine learning concepts and cloud platforms.
• Proficiency in Python or similar scripting languages.
• Experience with Docker and Kubernetes.
• Familiarity with CI/CD tools.

Responsibilities

• Develop automated workflows for building and deploying machine learning models.
• Ensure efficient model deployment and track performance in production.
• Manage ML infrastructure using code for consistency and scalability.
• Identify and resolve deployment and performance issues.
• Collaborate with data scientists to optimize models.

Skills

Machine Learning concepts

DevOps practices

Collaboration

Problem-solving

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

AWS

Azure

GCP

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: Bachelors 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.