Machine Learning Ops Engineer

On behalf of our client, a global organization driving digital transformation through technology and innovation, we are looking for an MLOps Engineer to join their AI operations team.

In this role, you’ll ensure AI and ML models run reliably, securely, and efficiently at scale. You’ll build and maintain pipelines that enable model training, deployment, and monitoring—turning prototypes into production-grade systems.

Key Responsibilities

• Design and manage CI/CD pipelines for ML models and AI services.
• Automate deployment workflows for training, testing, and serving models.
• Implement monitoring systems to track model performance, drift, and bias.
• Collaborate with Machine Learning Engineers to operationalize models effectively.
• Optimize infrastructure for scalability, reliability, and cost efficiency.
• Ensure compliance with data protection and security standards.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or related discipline (Master’s preferred).
• 3+ years of experience in MLOps or DevOps (MLflow, Kubeflow, or similar frameworks).
• Strong knowledge of containerization (Docker, Kubernetes) and CI/CD automation.
• Proficiency in Python, Bash, or equivalent scripting languages.
• Familiarity with monitoring and model lifecycle management tools.
• Excellent English communication skills; additional languages are an advantage.

Nice to Have

• Experience with feature stores, model registries, and data versioning.
• Understanding of responsible AI principles and auditability frameworks.
• Exposure to hybrid or multi-cloud environments.

What’s in it for you

• Competitive remuneration and flexible working environment.
• Free access to certifications and professional development programs.
• A culture of innovation, inclusivity, and collaboration.
• Clear paths for career progression in a growing AI ecosystem.