AI Platform Engineer — Scale ML in Production

Forestar Group; Arlington (TX); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Medical, Dental, Vision

401(K)

Employee Stock Purchase Plan

Paid Time Off & Holidays

Job summary

D.R. Horton, Inc. is seeking an AI Platform Engineer to advance our AI/ML platform. This role focuses on deploying scalable, secure AI workloads, building reusable services, and enabling teams to move from prototype to governed production quickly.

The ideal candidate will have hands-on experience with Python, containers, Kubernetes, CI/CD, and observability, and will contribute to architecture, governance, and advanced AI initiatives across the enterprise.

Qualifications

• Bachelor's degree in CS, Engineering, or related field or equivalent experience.
• 5+ years in ML engineering, MLOps, platform/cloud engineering or related field.
• Strong Python and containers, Kubernetes, APIs, CI/CD, IaC, observability experience.
• Production deployment of ML or generative AI workloads with model serving and governance.

Responsibilities

• Engineer AI/ML platform components: model serving, gateways, runtimes, and lifecycle management.
• Build reusable platform services for RAG, embeddings, vector search, agents, and observability.
• Automate environments, deployments, testing, rollbacks using CI/CD and IaC.
• Support hybrid cloud and on-prem AI infra with GPUs, containers, storage, and networking.
• Ensure AI platform reliability, security, performance, and FinOps practices.

Skills

Python

Kubernetes

CI/CD

MLOps

Cloud

Observability

Communication

Education

Bachelor's degree in CS or related field

Tools

Docker

Terraform

Git

Job description

D.R. Horton, Inc. is seeking an AI Platform Engineer to advance our AI/ML platform. This role focuses on deploying scalable, secure AI workloads, building reusable services, and enabling teams to move from prototype to governed production quickly.

The ideal candidate will have hands-on experience with Python, containers, Kubernetes, CI/CD, and observability, and will contribute to architecture, governance, and advanced AI initiatives across the enterprise.