Job Title: Machine Learning Engineer / MLOps Engineer
Experience: 5+ Years
Location: Hyderabad
Employment Type: Full-Time
About the Role
We are seeking a highly motivated and experienced Machine Learning Engineer / MLOps Engineer to join our growing AI and Data Science team. The ideal candidate will have robust expertise in building, deploying, and managing machine learning solutions at scale using AWS Sage Maker, MLflow, H2 O.ai, Py Spark, and MLOps best practices.
This role involves working closely with Data Scientists, Data Engineers, and Cloud Engineering teams to operationalize machine learning models, build robust ML pipelines, and ensure reliable model deployment, monitoring, and governance in production environments.
Key Responsibilities
Machine Learning Model Development & Deployment
Collaborate with Data Scientists to develop, train, validate, and deploy machine learning models.
Build scalable ML solutions using AWS Sage Maker and cloud-native services.
Implement model deployment strategies for real-time and batch inference workloads.




Support the full machine learning lifecycle from experimentation to production.
MLOps & Model Lifecycle Management
Design and implement end-to-end MLOps pipelines for model training, validation, deployment, monitoring, and retraining.
Establish CI/CD processes for machine learning workflows.
Automate model versioning, deployment, rollback, and governance processes.
Implement model monitoring, drift detection, and performance tracking mechanisms.
AWS Sage Maker & Feature Engineering
Develop and manage machine learning workflows using AWS Sage Maker.
Build and maintain feature engineering pipelines using Sage Maker Feature Store.
Optimize feature storage, retrieval, and reuse across machine learning projects.
Leverage Sage Maker capabilities for experimentation, training, deployment, and monitoring.
ML Experiment Tracking & Governance
Utilize MLflow for experiment tracking, model registry, model versioning, and lifecycle manage

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