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.
