ML Platform Engineer — Scale AI Infrastructure (Hybrid)

United States Digital Space LLC; Denver, California (CO, MO); Hybrid; USD 160,000 - 200,000; Full time

Job summary

the company is seeking a Machine Learning Platform Engineer to join the ML Platform team in Denver. You will build, scale, and operate ML/AI infrastructure and tools, ensuring reliable, scalable deployments for internal AI/ML workloads.

You will collaborate with AI/ML engineers to implement end-to-end pipelines, data workflows and model development support, while applying AI-native practices to improve product delivery and developer productivity.

Qualifications

• 5+ years of software engineering experience in Python, Ruby or Java.
• Experience designing and developing infrastructure and platform services for ML lifecycle.
• Experience with at least one major cloud platform (AWS preferred).
• Curiosity and experimentation with emerging AI frameworks and practices.

Responsibilities

• Build core components of ML and AI Platform roadmap with automated pipelines and standardized processes.
• Develop, maintain, and enhance frameworks for ML model development and deployment.
• Collaborate with ML/AI builders to determine requirements and SLAs for API-enabled services.
• Develop, maintain, and enhance infrastructure supporting ML services.
• Support deployment patterns for ML models with CI/CD pipelines and automated testing.
• Apply AI tools to engineering workflows and identify where AI can reduce effort and complexity.
• Adopt best practices for using AI technologies across development activities.

Skills

Python

Java

Ruby

MLOps

Cloud Infra

Tools

AWS

Job description

the company is seeking a Machine Learning Platform Engineer to join the ML Platform team in Denver. You will build, scale, and operate ML/AI infrastructure and tools, ensuring reliable, scalable deployments for internal AI/ML workloads.

You will collaborate with AI/ML engineers to implement end-to-end pipelines, data workflows and model development support, while applying AI-native practices to improve product delivery and developer productivity.