5 - 10 years

Hyderabad

Full time

Job Summary

We are looking for an experienced Machine Learning Engineer / MLOps Engineer to design, deploy, and maintain scalable machine learning solutions on Google Cloud Platform (GCP). The ideal candidate will have strong expertise in production ML systems, CI/CD automation, Vertex AI, and model lifecycle management while collaborating closely with cross-functional teams to operationalize machine learning models.

Key Responsibilities

Design, build, and maintain training and inference pipelines for storm outage prediction workflows.
Implement CI/CD, orchestration, and automation for machine learning workflows using Vertex AI and related GCP services.
Deploy machine learning models into production environments and manage model lifecycle processes, including versioning and rollout support.
Set up and maintain baseline monitoring for model drift, performance, reliability, and alerting.
Create scalable, production-ready ML workflows and supporting technical documentation.
Collaborate with data scientists, engineers,



and project stakeholders to operationalize models and align deployment architecture with project needs.
Support troubleshooting, performance tuning, and continuous improvement of ML platform components.
Contribute to engineering best practices across code quality, release processes, and environment stability.
Required Qualifications

5–10 years of experience in machine learning engineering, MLOps, or related production ML engineering roles.
Strong proficiency in Python and experience developing scalable data and ML workflows.
Hands-on experience with Google Cloud Platform, including Vertex AI, BigQuery, Cloud Storage, Cloud Run, Cloud Functions, or comparable services.
Experience with GitHub Actions or similar CI/CD tooling.
Demonstrated experience building CI/CD pipelines and automating ML model deployment and orchestration.
Experience with model monitoring, observability, and production support for machine learning

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