MLOps Engineer

Role

Key Responsibilities

• - Manage and automate AWS infrastructure using tools like Terraform/CDK/CloudFormation
• - Set up CI/CD pipelines for AI/ML model training and inference workflows
• - Optimize GPU and EC2 usage for high-performance computing workloads
• - Monitor infrastructure health, cost, and security
• - Collaborate with AI/ML teams to deploy models using SageMaker, ECS, EKS, or Lambda
• - Manage IAM roles, VPCs, networking, and data storage (S3, EFS, FSx)

Required Skills

• - 3+ years of AWS DevOps experience
• - Proficiency in infrastructure-as-code tools
• - Hands-on with Docker, GitHub Actions, Jenkins, or similar
• - Experience managing GPU instances and AI pipelines (e.g., SageMaker, Deep Learning AMIs)
• - Strong knowledge of Linux, networking, and cloud security best practices

Preferred

• - Exposure to ML Ops tools (MLflow, Kubeflow)
• - AWS Certifications (DevOps Engineer, Solutions Architect

  & responsibilities

Preferred candidate profile