Our Rochester, NY client is looking to hire an AWS ML Infrastructure Engineer to join their team on a contract basis!
This is a fully-remote/full-time/3-month contract position Hourly range based on experience: Up to $60/HR
Key Responsibilities:
Migrate ML inference workflows from Azure ML Studio to SageMaker Batch Transform (or equivalent service)
Move containerized application workloads to AWS using EKS, ALB, and CloudFront
Migrate VM disk images from Azure and set up corresponding VMs in AWS
Configure VPC access, including VPN connectivity
Set up AWS-integrated services on VMs to support ML labeling and training workflows (e.g., S3 mounts, file shares)
Migrate MLFlow and GeoServer instances to AWS
Use Terraform to provision and manage infrastructure components
Support Kubernetes-based orchestration and deployment workflows
Requirements:
5+ years of hands-on experience with AWS infrastructure and services
Strong experience with Terraform, Kubernetes, and EKS
Experience migrating machine learning infrastructure and applications from Azure to AWS
Proficiency in configuring VPNs, VPCs, and supporting hybrid environments
Familiarity with MLFlow, SageMaker (esp. Batch Transform), and related ML infrastructure
Ability to troubleshoot and optimize container-based workloads
Excellent communication and documentation skills
Applicants must be authorized to work in the U.S.
We are an equal-opportunity employer. We do not discriminate in hiring or employment against any individual based on race, color, gender, national origin, ancestry, religion, physical or mental disability, age, veteran status, sexual orientation, gender identity or expression, marital status, pregnancy, citizenship, or any other factor protected by anti-discrimination laws.