Description We are looking for a Senior MLOps Machine Learning Engineer with 6 years of experience to design build and scale our nextgeneration machine learning infrastructure In this role you will bridge the gap between Data Science and Core Engineering ensuring our predictive models move from experimental notebooks to highthroughput productiongrade systems seamlessly This isnt a role for standing up lowtraffic inference endpoints we deal with realworld scale You will work closely with data scientists to optimize distributed training using Ray orchestrate complex pipelines via Airflow Composer and manage scalable deployments on GCP If you love deepdiving into Python optimization writing clean Terraform code and architecture built for highvolume data and traffic this role is for you Requirements Seniority 6 years of experience in an MLOps DevOps or Data Engineering role with a heavy focus on productionizing machine learning models Python Mastery Exceptional Python programming skills with a deep understanding of asynchronous programming performance profiling and backend frameworks like FastAPI Production ML Scale Proven track record of deploying and monitoring ML models at scale You know how to handle highconcurrency traffic model drifting and resource optimization Cloud Data Proficiency Solid expertise in the GCP ecosystem and writing complex optimized SQL queries for large datasets Tooling Agility Comfortable working across a diverse ecosystem of package managers and frameworks with a keen interest in adopting highperformance tools like uv Education Bachelors or Masters degree in Computer Science Engineering Mathematics or a related technical field or equivalent practical experience Job responsibilities Infrastructure Automation Design provision and maintain scalable ML infrastructure on GCP using Terraform Scalable Deployment Architect and deploy highthroughput lowlatency M

📌 AI ML Engineer3 Nagpur
🏢 GlobalLogic
📍 Nagpur