MLOps Engineer (Senior)

Our client is seeking a Senior MLOps Engineer to build and support the infrastructure that enables machine learning solutions to operate reliably in production. This opportunity is ideal for an experienced professional who enjoys combining cloud engineering automation and machine learning operations to deliver scalable AI platforms.

Key Responsibilities:

• Build and maintain machine learning deployment pipelines.
• Automate model deployment monitoring and retraining processes.
• Implement CI/CD practices for machine learning applications.
• Manage model versioning governance and operational monitoring.
• Optimise cloud infrastructure supporting AI workloads.
• Collaborate with machine learning engineers data scientists and platform engineers.
• Improve reliability scalability and performance of production AI systems.
• Support continuous improvement of enterprise AI platforms.

Requirements:

• Bachelors degree in Computer Science Engineering Data Science or a related field.
• 10 years experience in DevOps cloud engineering or machine learning operations.
• Experience supporting production machine learning environments.
• Strong Python scripting and cloud platform experience.
• Experience with Docker Kubernetes CI/CD and Infrastructure as Code.
• Understanding of model lifecycle management and ML monitoring.
• Excellent troubleshooting and automation skills.

Advantageous

• Experience with MLflow Kubeflow or similar MLOps platforms.
• Azure or AWS certifications.
• Experience supporting enterprise AI environments.
• Knowledge of modern observability tools.

Personal Attributes:

• Detail-oriented and proactive.
• Passionate about automation and AI.
• Strong collaboration and communication skills.
• Excellent analytical and problem-solving ability.
• Dedicated to operational excellence.

Only shortlisted candidates will be contacted.
Submit your CV to or call .
Visit our website for more exciting career opportunities: will only be conducted with short listed candidates. Should you not hear from us within 4 days please consider your application unsuccessful.