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AI ML Engineer3 (Nagpur)

1.00 to 10.00 Years   Nagpur   31 Jul, 2026
GlobalLogic
Job LocationNagpur
EducationNot Mentioned
SalaryNot Disclosed
IndustryIT Services & Consulting
Functional AreaNot Mentioned
EmploymentTypeFull-time

Job Description

    Description We are looking for a Senior MLOps / Machine Learning Engineer with 6 years of experience to design, build, and scale our next-generation 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 high-throughput, production-grade systems seamlessly. This isnt a role for standing up low-traffic inference endpoints; we deal with real-world 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 deep-diving into Python optimization, writing clean Terraform code, and architecture built for high-volume 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 high-concurrency 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 high-performance 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 high-throughput, low-latency M .

Keyskills :
Machine LearningPythonDevOpsData EngineeringAirflowGCPSQLMLOpsRay

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