Job Title: AWS INFRASTRUCTURE ENGINEER / AI
Location: McleanVA
Duration: 12 Months
Visa: USC GC H1B and EAD
Contract Type: W2
Job Summary
We are looking for an AWS Infrastructure Engineer with AI experience to design deploy and operate scalable cloud infrastructure that supports AI/ML platforms and data-driven applications. This role sits at the intersection of cloud engineering DevOps and MLOps enabling teams to reliably train deploy and scale machine learning models on AWS.
Responsibilities
- Design and manage AWS cloud infrastructure for AI/ML workloads
- Build and maintain Infrastructure as Code using Terraform or CloudFormation
- Support model training inference and data pipelines
- Deploy and operate containerized workloads using Docker EKS or ECS
- Implement CI/CD pipelines for infrastructure and ML systems
- Optimize systems for cost performance and reliability
- Enforce security best practices (IAM networking encryption)
- Monitor log and troubleshoot production environments
- Collaborate with ML engineers data scientists and software teams
Required Qualifications
- Strong experience with AWS services (EC2 EKS/ECS S3 RDS VPC IAM Lambda)
- Hands-on experience supporting AI/ML platforms (SageMaker EKS-based ML stacks or similar)
- Experience with Terraform or other IaC tools
- Knowledge of Docker and Kubernetes
- Scripting skills (Python Bash)
- Solid understanding of cloud security and networking
Job Title: AWS INFRASTRUCTURE ENGINEER / AI Location: McleanVA Duration: 12 Months Visa: USC GC H1B and EAD Contract Type: W2 Job Summary We are looking for an AWS Infrastructure Engineer with AI experience to design deploy and operate scalable cloud infrastructure that supports AI/ML platforms ...
Job Title: AWS INFRASTRUCTURE ENGINEER / AI
Location: McleanVA
Duration: 12 Months
Visa: USC GC H1B and EAD
Contract Type: W2
Job Summary
We are looking for an AWS Infrastructure Engineer with AI experience to design deploy and operate scalable cloud infrastructure that supports AI/ML platforms and data-driven applications. This role sits at the intersection of cloud engineering DevOps and MLOps enabling teams to reliably train deploy and scale machine learning models on AWS.
Responsibilities
- Design and manage AWS cloud infrastructure for AI/ML workloads
- Build and maintain Infrastructure as Code using Terraform or CloudFormation
- Support model training inference and data pipelines
- Deploy and operate containerized workloads using Docker EKS or ECS
- Implement CI/CD pipelines for infrastructure and ML systems
- Optimize systems for cost performance and reliability
- Enforce security best practices (IAM networking encryption)
- Monitor log and troubleshoot production environments
- Collaborate with ML engineers data scientists and software teams
Required Qualifications
- Strong experience with AWS services (EC2 EKS/ECS S3 RDS VPC IAM Lambda)
- Hands-on experience supporting AI/ML platforms (SageMaker EKS-based ML stacks or similar)
- Experience with Terraform or other IaC tools
- Knowledge of Docker and Kubernetes
- Scripting skills (Python Bash)
- Solid understanding of cloud security and networking
View more
View less