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Scaffold

AI-driven contractor coordination across builder systems

Senior Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeAustin, TX, USAIn-person

About the Job

Requirements

  • Three to six or more years of experience in machine learning engineering, applied artificial intelligence, or related roles.
  • Strong programming skills, with Python required; familiarity with Node or TypeScript is a plus.
  • Experience building and deploying machine learning models in production environments.
  • Familiarity with large language models, prompt engineering, and modern artificial intelligence tooling.
  • Strong understanding of data pipelines, application programming interfaces, and distributed systems.

Responsibilities

  • Design and deploy machine learning models that operate on real-world construction data.
  • Develop large-language-model-powered workflows for document parsing, communication, and automation.
  • Build intelligent agents that interact with external systems, including builder portals and enterprise resource planning systems.
  • Ingest, clean, and structure messy third-party data.
  • Train, evaluate, and iterate on models in production.
  • Design feedback loops to continuously improve model performance.
  • Integrate machine learning systems into backend services and application programming interfaces.
  • Collaborate on data pipelines and infrastructure.
  • Partner with frontend engineers to expose artificial intelligence capabilities in the product.
  • Evaluate model approaches, including large language models, fine-tuning, retrieval, and traditional machine learning.
  • Define scalable patterns for deploying artificial intelligence across customers.
  • Contribute to the long-term artificial intelligence roadmap and product direction.
  • Work closely with product, engineering, and customers.
  • Translate ambiguous problems into production-ready solutions.
  • Provide technical leadership on artificial intelligence initiatives.

Desired Qualifications

  • Experience with large language model frameworks such as LangChain and LlamaIndex.
  • Experience with vector databases and retrieval systems.
  • Experience with data processing at scale using tools such as Spark and Airflow.
  • Exposure to real-world noisy data environments, rather than only clean datasets.
  • Experience building internal tools or automation systems.

About the Company

Scaffold

AI-driven contractor coordination across builder systems

Scaffold helps homebuilders coordinate a wide network of trade contractors using AI that connects to the systems contractors already use, including portals for 29 of the top 30 U.S. homebuilders. It keeps a single up-to-date record for each job and automates common project tasks such as purchase orders, schedules, change orders, and discrepancy detection. This reduces repetitive work and miscommunications that lead to dry runs and paperwork thrash, helping crews stay on schedule on hundreds of thousands of homes. Scaffold differentiates itself by integrating with existing builder and contractor systems rather than replacing builder portals, enabling collaboration across builders, contractors, and suppliers. The company aims to improve efficiency in the roughly $500 billion homebuilding industry, expanding coverage and engineering to support more integrated workflows for builder, contractor, and supplier systems.

Company size
11-50
Company stage
Seed
Total funding
$15M
Headquarters
Austin, TX
Founded
2024

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