Artificial Intelligence (AI) & Machine Learning Engineer

About the Role

Key Responsibilities

• · Design, deploy, and maintain scalable AI/ML systems and infrastructure.
• · Develop and manage MLOps pipelines for automated model deployment and monitoring.
• · Ensure the performance, reliability, security, and scalability of AI platforms.
• · Deploy, serve, and optimize machine learning and generative AI models for production environments.
• · Build and maintain CI/CD pipelines for AI applications.
• · Manage containerized AI applications using Docker and Kubernetes.
• · Collaborate with data scientists, software engineers, and business stakeholders to operationalize AI solutions.
• · Monitor AI system performance, reliability, and availability, implementing continuous improvements.
• · Troubleshoot production issues and optimize AI infrastructure.

Requirements

• · Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
• · 3–8 years of experience in AI systems engineering, MLOps, or machine learning platform engineering.
• · Strong programming skills in Python.
• · Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
• · Hands-on experience with Docker, Kubernetes, and containerized deployments.
• · Experience designing and maintaining CI/CD pipelines.
• · Knowledge of distributed systems and scalable AI infrastructure.
• · Experience deploying and operationalizing machine learning and generative AI solutions.

Preferred Qualifications

• · Experience with Azure Machine Learning, AWS SageMaker, or Google Vertex AI.
• · Experience with Infrastructure as Code (Terraform or similar).
• · Familiarity with AI monitoring, observability, and model lifecycle management.
• · Relevant cloud or AI certifications.