AWS AI/ML Engineer — Build Production-Grade ML on AWS

Robotics Technologies; Austin (TX); On-site; USD 89,000 - 126,000; Full time

Job summary

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

The role focuses on end-to-end AWS ML pipelines, IaC, cost/performance optimization, and secure practices.

Qualifications

• 4+ years of AI/ML and cloud platform engineering with hands-on AWS experience.
• 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.
• Proficiency in Python and containerization (Docker)

Responsibilities

• Design end-to-end ML pipelines on AWS (SageMaker, Bedrock, ECS, Lambda, Step Functions, etc.) 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 inference 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

Python

ML lifecycle

AWS Cloud

Tools

Docker

Kubernetes

Terraform

CodePipeline

GitHub Actions

GitLab CI

SageMaker

Bedrock

Job description

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

The role focuses on end-to-end AWS ML pipelines, IaC, cost/performance optimization, and secure practices.