Machine Learning Engineer

Job Title: MLOps Engineer (L3/L4) Experience: 5–8 Years Location: Flexible/Hybrid Job Summary We are looking for an experienced MLOps Engineer (L3/L4) with 5–8 years of experience to build, deploy, monitor, and manage machine learning solutions in production. The ideal candidate should have strong expertise in cloud platforms, CI/CD, containerization, automation, and machine learning lifecycle management. Key Responsibilities Design, build, and maintain scalable MLOps pipelines. Deploy and manage machine learning models in production. Develop CI/CD pipelines for ML workflows. Automate model training, testing, deployment, and monitoring. Work closely with Data Scientists, Data Engineers, and Software Engineers. Monitor model performance and ensure reliability and scalability. Manage infrastructure using Infrastructure as Code (IaC). Implement security, governance, and best practices for ML platforms. Troubleshoot production issues and optimize ML systems. Required Skills 5–8 years of experience in MLOps, DevOps, or Machine Learning Engineering. Strong experience with Azure Machine Learning, Azure DevOps, or Databricks. Good knowledge of Python and SQL. Experience with Docker and Kubernetes. Hands-on experience with CI/CD tools such as Azure DevOps, GitHub Actions, or Jenkins. Knowledge of ML lifecycle management and model deployment. Experience with Git version control. Familiarity with Terraform or other Infrastructure as Code tools. Understanding of monitoring tools such as Prometheus, Grafana, or Azure Monitor. Preferred Skills Experience with MLflow. Knowledge of Apache Airflow or similar workflow orchestration tools. Experience with Spark and Databricks. Knowledge of REST APIs and microservices. Understanding of cloud security and governance. Experience with Generative AI or Large Language Model (LLM) deployment is an added advantage. Qualifications Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, or a related field. Relevant Azure, Kubernetes, or Databricks certifications are preferred. Good to Have Strong communication and problem-solving skills. Experience working in Agile/Scrum environments. Ability to collaborate with cross-functional teams. Experience supporting enterprise-scale machine learning platforms.