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DevOps & Data Engineer (ML Infrastructure & Analytics)

DevOps & Data Engineer (ML Infrastructure & Analytics)

withRemote

4 - 8 years

10 - 12 Lacs

bengaluru

Posted:20 hours ago| Platform:

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Skills Required

data engineering devops terraform redshift aws aws cloudformation amazon ec2 kafka microsoft flow amazon cloudwatch encryption datadog security grafana mlops aws devops iam ansible cloud infrastructure monitoring kubernetes

Work Mode

Remote

Job Type

Full Time

Job Description

Title:

Salary:

Working Days:

Working Hours:

Contract Duration:

Location:

JD:

Design and implement the multi-tenant cloud infrastructure on AWS
Deploy and scale SLM instances across GPU-enabled infrastructure
Implement MLOps pipelines for model training, deployment, and monitoring
Ensure security, compliance, and data isolation across tenants
Set up monitoring, alerting, and performance optimization

Screening Parameters:

Must have deployed multi-tenant SaaS applications
Production experience with data warehouse setup (Redshift)
ML model deployment and scaling experience or any AI model deployment experience
Infrastructure as code and automation expertise
Security and compliance implementation

Projects Must Have/Done:

Deployed and scaled a multi-tenant B2B SaaS platform
Built data warehouse and ETL pipelines for analytics
Managed ML model deployment and inference serving
Implemented complete CI/CD with security scanning
Production Kubernetes and container orchestration

TechStack:

Infrastructure: Terraform, CloudFormation, Ansible
Cloud: AWS (EC2, EKS, S3, RDS)
Data: Redshift, dbt, Airflow, Spark, Kafka
MLOps: Kubernetes, Docker, MLflow, Kubeflow, Prometheus
Monitoring: Grafana, Datadog, CloudWatch, ELK Stack
Security: VPC, IAM, encryption, SOC 2 compliance

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