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ML Ops Engineer

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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

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