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D.R. Horton

Builds and sells single-family homes across the US

AI Platform Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeArlington, TX, USANo salary listed

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience.
  • At least five years of experience in machine learning engineering, MLOps, platform engineering, cloud engineering, DevOps, or related work.
  • Strong Python skills and experience with containers, Kubernetes or comparable orchestration, APIs, continuous integration and continuous delivery, infrastructure as code, and observability.
  • Experience deploying and operating machine learning or generative AI workloads in production.
  • Working knowledge of model serving, retrieval-augmented generation, vector databases or search, large language model gateways and model routing, agent frameworks and tool or Model Context Protocol integration, evaluation, large language model observability including traces, tokens, latency, and cost per task, security, and AI workload economics.
  • Ability to build trusted relationships across the organization while balancing enterprise standards with business needs and operating realities.
  • Ability to work independently, take ownership, communicate clearly, and deliver results in an evolving environment.
  • Ability to travel overnight.

Responsibilities

  • Engineer model and large language model deployment, inference, serving, gateway, evaluation, monitoring, registry, and lifecycle capabilities.
  • Build reusable platform services for retrieval-augmented generation, embeddings, vector search, agents, secrets, API access, workload isolation, quotas, and observability.
  • Automate environments, deployments, testing, rollback, and infrastructure using continuous integration and continuous delivery and infrastructure as code.
  • Support hybrid cloud and on-premises AI infrastructure, including GPU-enabled compute, containers, storage, networking, scheduling, and capacity management.
  • Establish AI platform reliability, security, performance, utilization, and financial operations practices.
  • Represent the function in cross-functional discovery, architecture, governance, operational readiness, and continuous improvement activities as appropriate.
  • Stay current on relevant data, AI, digital, software, and industry practices and apply new capabilities when they create practical business value.
  • Identify, shape, and pilot opportunities where data, AI, and digital capabilities can create business value by building, testing, and learning quickly.
  • Conduct business professionally and ethically to serve customers and increase the goodwill and profit of the company.

Desired Qualifications

  • Experience with Azure, Microsoft Foundry or comparable AI gateways and model routers, NVIDIA AI Enterprise and GPU infrastructure, vLLM/NIM or comparable open-weight model serving, Snowflake AI capabilities, MLflow, Kubernetes, or Model Context Protocol or comparable technologies.
  • Experience in homebuilding, real estate, construction, mortgage, title, land development, sales, purchasing, finance, customer care, or another distributed operating business.
  • Experience working in a large enterprise with complex enterprise environments.
  • Experience founding, incubating, or building new products, capabilities, or businesses from the ground up.

About the Company

D.R. Horton

Builds and sells single-family homes across the US

D.R. Horton builds and sells single-family homes, townhomes and condominiums across the United States, mostly for first-time and move-up buyers. Most revenue comes from selling homes it builds on land it buys or controls through purchase contracts, with local divisions managing land, construction and sales. Its own mortgage lender, DHI Mortgage, and its title agency earn fees by financing and closing many of those purchases. The company also builds single-family and multifamily rental communities and sells them to investors once they are leased, adding a second home-sales channel. It was founded in 1978 in Texas and is headquartered in Arlington, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Arlington, TX
Founded
1978

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