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.

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