AI/ML Engineer — Production ML on AWS

Quantum Technologies LLC; Austin (TX); On-site; USD 95,000 - 136,000; Full time

Job summary

Quantum Technologies LLC seeks an experienced AI/ML Engineer to design, build, and operate production-grade ML systems on AWS in Austin, TX. You will own the full ML lifecycle—from experiment tracking and model training to secure, scalable deployment and monitoring—collaborating with data scientists, platform, and security teams.

The role emphasizes cost optimization, robust monitoring, and compliance, with on-call rotation for production ML systems and strong emphasis on reproducibility and

Qualifications

• 4+ years of AI/ML and cloud platform 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 (CodePipeline, GitHub Actions, GitLab CI, or equivalent) and infrastructure-as-code (Terraform preferred).
• Solid understanding of ML lifecycle concepts: experiment tracking, model versioning, serving patterns (real-time, batch, streaming), and monitoring for data/model drift.

Responsibilities

• Design and maintain end-to-end ML pipelines on AWS (SageMaker, Bedrock, ECS, Lambda, Step Functions, etc.) for training, evaluation, deployment, and inference.
• Implement infrastructure-as-code (Terraform/CloudFormation) and CI/CD pipelines for ML workloads, including model packaging, versioning, and promotion across environments.
• Build robust model monitoring, drift detection, logging, and ing solutions (CloudWatch, SageMaker Model Monitor, custom metrics).
• Optimize cost, performance, and reliability of training and inference workloads (spot instances, multi-instance training, autoscaling, batch vs. real-time endpoints).
• Establish secure AI/ML practices: least-privilege IAM, KMS encryption, network isolation, secret management, and compliance controls for model artifacts and data.
• Collaborate with data scientists to produce production grade models, improve reproducibility, and reduce time-to-deployment.
• Maintain model registries, feature stores, experiment tracking, and artifact lineage.
• Document architecture, runbooks, and operational procedures; participate in on-call rotation for production ML systems.

Skills

AI/ML experience

AWS cloud

Python

Containerization

Tools

SageMaker

Bedrock

EC2

ECS

EKS

S3

IAM

VPC

CloudWatch

Lambda

Step Functions

Terraform

CloudFormation

CodePipeline

GitHub Actions

GitLab CI

Docker

Kubernetes

Job description

Quantum Technologies LLC seeks an experienced AI/ML Engineer to design, build, and operate production-grade ML systems on AWS in Austin, TX. You will own the full ML lifecycle—from experiment tracking and model training to secure, scalable deployment and monitoring—collaborating with data scientists, platform, and security teams.

The role emphasizes cost optimization, robust monitoring, and compliance, with on-call rotation for production ML systems and strong emphasis on reproducibility and