Senior 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) - 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.