SageMaker Platform Engineer

ComTec Information Systems (IT); Plano (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

ComTec Information Systems (IT) is seeking a SageMaker Platform Engineer to design, deploy, and optimize AWS SageMaker environments. You will partner with data scientists to support ML workflows and ensure scalable, secure infrastructure.

Key focus areas include Studio Classic and exposure to Uniform Studio, building reliable pipelines, monitoring models, and maintaining platform health. The role demands hands-on AWS/SageMaker expertise and a strong foundation in ML concepts, with a

Qualifications

• 4–5 years hands-on SageMaker Studio Classic experience.
• Strong background in ML concepts and workflows.
• Experience setting up and configuring SageMaker platforms.
• Exposure to Uniform Studio preferred.
• Deep knowledge of AWS services, especially SageMaker.

Responsibilities

• Design, implement, and manage AWS SageMaker environments.
• Support ML workflows, including model training, deployment, and monitoring.
• Collaborate with data scientists and engineers to optimize ML pipelines.
• Ensure platform scalability, security, and performance.
• Troubleshoot and resolve platform-related issues.

Skills

AWS SageMaker

SageMaker Studio Classic

Uniform Studio

Machine Learning

ML Pipelines

Job description

Overview

We are seeking a highly skilled Platform Engineer with deep expertise in AWS SageMaker and Machine Learning. The ideal candidate will have strong experience in setting up, managing, and optimizing SageMaker environments, with a focus on Studio Classic and exposure to Uniform Studio.

Job Title: SageMaker Platform Engineer

We are seeking a highly skilled Platform Engineer with deep expertise in AWS SageMaker and Machine Learning. The ideal candidate will have strong experience in setting up, managing, and optimizing SageMaker environments, with a focus on Studio Classic and exposure to Uniform Studio.

Key Responsibilities

• Design, implement, and manage AWS SageMaker environments.
• Support Machine Learning workflows, including model training, deployment, and monitoring.
• Collaborate with data scientists and engineers to optimize ML pipelines.
• Ensure platform scalability, security, and performance.
• Troubleshoot and resolve platform-related issues.

Required Skills & Experience

• AWS Expertise: Deep knowledge of AWS services, particularly SageMaker.
• SageMaker Studio Classic: 4–5 years of hands‑on experience.
• Uniform Studio: Exposure preferred.
• Strong background in Machine Learning concepts and workflows.
• Ability to set up and configure SageMaker platforms.

Interview Focus

• AWS services and SageMaker expertise.
• Hands‑on platform setup and troubleshooting.