Senior Machine Learning Engineer

About the role

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

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