AWS AI/ML Engineer — Build Production ML on AWS

Cloud Analytics Technologies, LLC; Austin (TX); On-site; USD 91,000 - 124,000; Full time

Job summary

Cloud Analytics Technologies, LLC seeks an experienced AWS AI/ML Engineer to design and operate production-grade ML systems on AWS. You will own the full ML lifecycle—from experiment tracking to deployment, monitoring, and ongoing improvement—collaborating with data scientists, platform, and security teams.

You will design end-to-end pipelines using SageMaker, Bedrock, and AWS services, implement IaC and CI/CD, and ensure secure, scalable ML workflows with proper governance and observability.

Qualifications

• 4+ years of AI/ML and cloud engineering with significant hands-on AWS work.
• Strong proficiency with AWS ML and infrastructure services (SageMaker, Bedrock, EC2, ECS/EKS, S3, IAM, VPC, CloudWatch, Lambda, Step Functions).
• Experience building and operating CI/CD pipelines for ML and infrastructure-as-code (Terraform preferred).
• Solid understanding of ML lifecycle concepts: experiment tracking, model versioning, serving patterns, and monitoring for data/model drift.
• Proficiency in Python and containerization (Docker, Kubernetes/EKS/ECS).
• Familiarity with security best practices for ML systems (IAM least privilege, encryption, network controls, audit logging).

Responsibilities

• Design and maintain end-to-end ML pipelines on AWS for training, evaluation, deployment, and inference.
• Implement infrastructure-as-code (Terraform/CloudFormation) and CI/CD pipelines for ML workloads.
• Build robust model monitoring, drift detection, logging, and ing solutions (CloudWatch, SageMaker Model Monitor).
• Optimize cost, performance, and reliability of training and inference workloads.
• Establish secure AI/ML practices and governance for model artifacts and data.
• Collaborate with data scientists to produce production-grade models and reproducibility.
• Maintain model registries, feature stores, experiment tracking, and artifact lineage.
• Document architecture, runbooks, and operational procedures; participate in on-call rotation.

Skills

AWS

Python

CI/CD

Terraform

Machine Learning

Docker

Kubernetes

Security

Tools

SageMaker

Bedrock

EC2

ECS

EKS

S3

IAM

VPC

CloudWatch

Lambda

Step Functions

Terraform

Job description

Cloud Analytics Technologies, LLC seeks an experienced AWS AI/ML Engineer to design and operate production-grade ML systems on AWS. You will own the full ML lifecycle—from experiment tracking to deployment, monitoring, and ongoing improvement—collaborating with data scientists, platform, and security teams.

You will design end-to-end pipelines using SageMaker, Bedrock, and AWS services, implement IaC and CI/CD, and ensure secure, scalable ML workflows with proper governance and observability.