Artificial Intelligence (AI) & Machine Learning Engineer

About the Role Design, deploy, and maintain scalable AI and machine learning systems that deliver secure, reliable, and high-performing AI solutions. Ensure efficient model serving, deployment, monitoring, and operational excellence across AI environments. 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.