Senior Machine Learning Engineer

Machine Learning Engineer 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), and 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. Scaffold Service Inc