Machine Learning Engineer

Messilat; Dubai; On-site; AED 60,000 - 100,000; Full time

Job summary

An innovative firm is on the lookout for a skilled MLOps Engineer to join their dynamic team. This role offers the opportunity to deploy machine learning models and manage microservices using cutting-edge technologies like Docker and Kubernetes. You will collaborate with cross-functional teams to ensure models are scalable and high-performing. If you are passionate about optimizing AI applications and making a significant impact in the field of MLOps, this is the perfect opportunity for you to grow and thrive in a challenging environment.

Qualifications

• 3+ years of experience in MLOps or a related field.
• Expertise in model deployment and containerization.

Responsibilities

• Transition models from development to production with high performance.
• Implement monitoring strategies for deployed models.

Skills

MLOps

Model Deployment

Docker

Kubernetes

AWS Cloud Services

Collaboration

Tools

Docker

Kubernetes

AWS

Job description

Messilat is seeking a talented MLOps Engineer for our client's team. The perfect candidate will excel in deploying models, managing microservices, utilizing Docker, and maintaining Kubernetes. Our client is also exploring AI applications in customer service, cybersecurity, and compliance.

Key Responsibilities

• Transition models from development to production, ensuring scalability and high performance. Collaborate with development teams for seamless model deployment.
• Implement monitoring and maintenance strategies for deployed models to ensure ongoing accuracy and reliability.
• Maintain Kubernetes clusters to ensure high availability and performance.
• Work with cross-functional teams to understand business requirements and deliver effective machine learning solutions.
• Develop and implement strategies that optimize efficiency and data quality.

Qualifications

• Minimum of 3 years of experience in MLOps or a related field.
• Expertise in model deployment, containerization, and orchestration (e.g., Docker, Kubernetes).
• Familiarity with cloud platforms (e.g., AWS, or on-premises) for model deployment and management.
• Experience in deploying AI models and managing their lifecycle.
• Proficiency in Python for scripting and automation.
• Prior experience in addressing scalability and pricing concerns in ML operations.

Skills

• Model deployment, monitoring, Docker, Kubernetes, AWS Cloud services, on-premises deployment, collaboration.

If you are passionate about MLOps and looking for a challenging role where you can make a significant impact, we would love to hear from you. Apply today!