ML Ops Engineer

Title: ML Ops Enigneer

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

Job Description:

• 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, Contractual / Temporary
Contract length: 3 months

Pay: ₹1,000,000.00 - ₹1,200,000.00 per year

Work Location: Remote