Title: DevOps \& Data Engineer - ML Infrastructure \& Analytics
Salary: upto 100,000 per month, depending on experience and skills
Working Days: Monday to Saturday
Working Hours: 5PM to 2AM
Contract Duration: 3 months (with potential extension based on performance, project need)
Location: Remote
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
Job Types: Full-time, Permanent
Pay: ₹1,000,000.00 - ₹1,200,000.00 per year
Work Location: Remote