MLOps Engineer

Working closely with Data Scientists, Data Engineers, and DevOps teams, you will help bring AI solutions from experimentation to production.

What's in It for You?

• Work on cutting-edge AI and Machine Learning initiatives.
• Collaborate with highly skilled technology professionals.
• Exposure to modern cloud, automation, and MLOps technologies.
• Opportunities for career growth and continuous learning.
• Competitive salary and benefits package.
• Dynamic and innovation-focused work environment.

• Design, implement, and maintain end-to-end ML deployment pipelines.
• Automate model training, testing, deployment, and monitoring processes.
• Build and manage scalable cloud-based ML infrastructure.
• Monitor model performance and ensure reliability in production environments.
• Implement CI/CD best practices for machine learning workflows.
• Collaborate with Data Scientists to operationalise machine learning models.
• Manage model versioning, governance, and lifecycle processes.
• Ensure security, scalability, and performance of AI platforms.

• Bachelor's Degree in Computer Science, Engineering, Data Science, or a related field.
• 3+ years of experience in MLOps, DevOps, Data Engineering, or Machine Learning Engineering.
• Strong experience with Python and scripting languages.
• Hands-on experience with cloud platforms such as Azure, AWS, or Google Cloud.
• Experience with containerisation technologies such as Docker and Kubernetes.
• Knowledge of CI/CD pipelines and Infrastructure as Code.
• Experience with ML lifecycle tools such as MLflow, Kubeflow, Airflow, or similar.
• Familiarity with machine learning frameworks and production deployment processes.
• Strong troubleshooting, automation, and problem-solving skills.

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