We are hiring a Machine Learning Engineer to design, build, and deploy AI systems that sit at the core of Scaffold’s platform.
This is not a “model-only” role. You will operate as a product-minded engineer, working across data pipelines, model development, and production systems to deliver real-world impact.
You will help define how AI is applied across:
Workflow automation (POs, schedules, change orders)
Data normalization and enrichment
Predictive insights (delays, risk, capacity)
Agent-based systems interacting with builder/trade ecosystems
About Scaffold
Scaffold is building the data orchestration layer for residential construction. We integrate fragmented systems across builders, subcontractors, and suppliers to automate workflows, eliminate manual work, and unlock real-time decision-making.
We are now embedding AI deeply into this system — transforming raw, messy construction data into intelligent automation, predictive insights, and agent-driven workflows.
What You’ll Do:
Build AI-Powered Product Features
Design and deploy machine learning models that operate on real-world construction data
Develop LLM-powered workflows for document parsing, communication, and automation
Build intelligent agents that interact with external systems (builder portals, ERPs
Own the End-to-End ML Lifecycle
Ingest, clean, and structure messy third-party data
Train, evaluate, and iterate on models in production
Design feedback loops to continuously improve performance
Work Across the Stack
Integrate ML systems into backend services and APIs
Collaborate on data pipelines and infrastructure
Partner with frontend engineers to expose AI capabilities in product
Drive Architecture & Strategy
Evaluate model approaches (LLMs, fine-tuning, retrieval, traditional ML)
Define scalable patterns for deploying AI across customers
Contribute to long-term AI roadmap and product direction
Collaborate Cross-Functionally
Work closely with product, engineering, and customers
Translate ambiguous problems into production-ready solutions
Provide technical leadership on AI initiatives
What We’re Looking For:
Core Requirements
3–6+ years of experience in ML engineering, applied AI, or related roles
Strong programming skills (Python required; familiarity with Node/TypeScript a plus)
Experience building and deploying ML models in production environments
Familiarity with LLMs, prompt engineering, and modern AI tooling
Strong understanding of data pipelines, APIs, and distributed systems
Preferred Experience
Experience with:
LLM frameworks (LangChain, LlamaIndex, etc.)
Vector databases / retrieval systems
Data processing at scale (Spark, Airflow, etc.)
Exposure to real-world noisy data environments (not just clean datasets)
Experience building internal tools or automation systems
Mindset
Product-oriented: you care about outcomes, not just models
Systems thinker: you design for scale and reliability
Builder: you take ownership and move fast in ambiguous environments
Curious: you stay on the frontier of AI capabilities
Why Join Scaffold?
Impact: Play a critical role in defining and building the future of Scaffold and the residential construction industry.
Growth Opportunity: Be an early leader in a venture-backed company.
Culture: Work alongside high-caliber teammates in a no-ego, high-energy environment.
Compensation: Competitive salary and meaningful equity in the company.
Skills Required
- 3-6+ years of experience in machine learning engineering, applied AI, or related roles
- Strong programming skills in Python
- Experience building and deploying machine learning models in production environments
- Familiarity with large language models, prompt engineering, and modern AI tooling
- Strong understanding of data pipelines, APIs, and distributed systems
- Familiarity with Node.js or TypeScript
- Experience with LLM frameworks such as LangChain or LlamaIndex
- Experience with vector databases or retrieval systems
- Experience with large-scale data processing tools such as Spark or Airflow
- Exposure to noisy real-world data environments
- Experience building internal tools or automation systems
What We Do
Scaffold builds an AI-powered data integration and automation platform for residential homebuilding. Its system translates data from homebuilders, subcontractors, and suppliers into a common format, turning messy builder data into structured workflows. It automates schedules, purchase orders, and job coordination, helping specialty contractors and suppliers reduce manual data entry and errors, respond faster, and lower operational overhead when managing work across multiple builders.
