AWS AI/ML Engineer: Production ML Pipelines

Quantum Technologies LLC; Sunnyvale (CA); On-site; USD 83,000 - 131,000; Full time

Job summary

Quantum Technologies. LLC is seeking an experienced AI/ML Engineer to design, build, and operate production-grade ML systems on AWS. You will own the full ML lifecycle—from experiment tracking to deployment—while partnering closely with data scientists, platform, and security teams.

Responsibilities include designing end-to-end ML pipelines on AWS, implementing IaC and CI/CD, building monitoring and cost-optimization, and ensuring secure practices across model artifacts and data.

Qualifications

• 4+ years of AI/ML and cloud platform engineering with hands-on AWS experience.
• Proficiency with AWS services (SageMaker, Bedrock, EC2, ECS/EKS, S3, IAM, VPC, CloudWatch, Lambda, Step Functions).
• Experience building 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 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 and CI/CD pipelines for ML workloads, including model packaging, versioning, and promotion across environments.
• Build robust model monitoring, drift detection, logging, and alerting 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 Engineering

AWS Cloud

Python

Docker

Kubernetes

CI/CD

Security Best Practices

Tools

Terraform

CloudFormation

SageMaker

Bedrock

EC2

ECS/EKS

S3

IAM

VPC

CloudWatch

Job description

Quantum Technologies. LLC is seeking an experienced AI/ML Engineer to design, build, and operate production-grade ML systems on AWS. You will own the full ML lifecycle—from experiment tracking to deployment—while partnering closely with data scientists, platform, and security teams.

Responsibilities include designing end-to-end ML pipelines on AWS, implementing IaC and CI/CD, building monitoring and cost-optimization, and ensuring secure practices across model artifacts and data.