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MLOps Engineer - Openkyber
MLOps Engineer
Senior MLOps Engineer with deep expertise in AWS and Amazon SageMaker, responsible for building, deploying, and monitoring production ML pipelines, model registry, feature store, and multi‑tenant environments.
About the role
Key Responsibilities
- Design, implement, and maintain end‑to‑end MLOps pipelines on AWS, leveraging SageMaker Studio, Pipelines, and Feature Store.
- Manage model lifecycle: training, versioning, deployment, rollback, and monitoring across multiple projects.
- Configure and optimize multi‑tenant SageMaker environments, including blueprints and domain/project setups.
- Collaborate with data scientists and software engineers to integrate ML models into production services.
- Ensure compliance with security, governance, and cost‑management best practices in cloud infrastructure.
Requirements
- 10–15 years of software engineering experience focused on cloud infrastructure or ML platform operations.
- 5+ years hands‑on experience with AWS, including deep expertise in Amazon SageMaker.
- 3+ years building and operating production MLOps pipelines (training, versioning, deployment, monitoring, rollback).
- Strong knowledge of SageMaker Unified Studio or Studio Classic, domain/project setup, and multi‑tenant configuration.
- Proven ability to troubleshoot and optimize ML workflows at scale.