ML Ops Engineer (Bengaluru)

ML Ops Engineer (Bengaluru)

16 Sep
|
Guddge Infosol
|
Bengaluru

16 Sep

Guddge Infosol

Bengaluru

ob Title: MLOps Engineer AWS | Terraform | SageMaker

Experience: 3+ Years
Location: Remote / Offshore (India) Work hours aligned to US Pacific Time (approx. 8:00 PM – 5:00 AM IST)
Employment Type: Full-Time, Permanent
Role Category: IT Consulting / Cloud Consultant
Industry: IT Services & Consulting

About the Role

We're hiring an MLOps Engineer to own the reliability, deployment, and monitoring of a production ML pipeline that powers daily risk scores used by operational leaders to prevent incidents before they happen. This is a hands-on infrastructure and operations role — the model is trained offline; your job is to keep the scoring pipeline dependable, observable, secure, and easy to evolve.

You'll work across a modern AWS stack (S3, Glue, SageMaker, Step Functions) backed by a fully automated Terraform + GitHub Actions delivery pipeline spanning multiple environments.

What You'll Do
- Operate and improve an end-to-end inference pipeline (SAP HANA AWS Glue SageMaker Step Functions SAP HANA), ensuring reliable scheduled daily runs
- Own infrastructure-as-code:



maintain Terraform modules, manage remote state via Terraform Cloud, and promote changes across dev qa prd
- Build and maintain CI/CD workflows in GitHub Actions
- Ensure full pipeline observability through structured JSON logging, CloudWatch Logs Insights, and Step Functions execution monitoring
- Support model drift detection and data-quality checks; tune alert thresholds and triage failures
- Troubleshoot production incidents (DB connectivity, SageMaker job failures, Glue write-back, scheduler issues) using established runbooks and drive root-cause resolution
- Enforce security and compliance: encryption, least-privilege IAM, secrets management, and no-PII-in-logs discipline
- Partner with data scientists to deploy retrained models via SageMaker Model Registry and cross-account promotion

Must-Have Skills
- 3+ years of MLOps experience supporting production systems
- Solid hands-on AWS experience, e

📌 ML Ops Engineer (Bengaluru)
🏢 Guddge Infosol
📍 Bengaluru

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