Job Description

To design, build, deploy and support Machine Learning, AI and Generative AI solutions in production. The role will focus on turning AI/ML models and prototypes into scalable, reliable and business-ready solutions. Key Responsibilities Build and deploy Machine Learning and AI solutions into production. Develop ML pipelines using Databricks and MLflow. Build GenAI, LLM, RAG and AI Agent solutions. Deploy AI/ML solutions on Azure and AKS. Develop APIs and microservices for AI/ML applications. Use Docker and Kubernetes for scalable deployments. Implement MLOps, CI/CD, testing and monitoring. Monitor, troubleshoot and optimize production AI/ML solutions. Work with Data Scientists to move models from development into production. Collaborate with Cloud, Infrastructure, Security and Technology teams. Mentor junior engineers and contribute to best practices. Key Deliverables Production-ready ML models and pipelines. Deployed GenAI, LLM, RAG and AI Agent solutions. AI/ML applications and APIs running on Azure/AKS. Automated deployment, testing and monitoring processes. Secure, scalable and reliable AI/ML solutions. Requirements Relevant degree in Computer Science, Engineering, Data Science, Econometrics, Mathematical Statistics, Actuarial Science or a related field. Senior-level experience in Machine Learning Engineering, AI Engineering, MLOps or a related technical role. Proven experience deploying and supporting AI/ML solutions in production. Strong experience with Python. Hands-on experience with Databricks and MLflow. Experience with Azure and AKS. Experience with Docker and Kubernetes. Experience with MLOps and CI/CD. Experience with Generative AI, LLMs, RAG and/or AI Agents. Experience developing REST APIs and microservices.