Build production AI for our Real Estate vertical. Own the AVM model, extend a multi-agent property intelligence pipeline, and ship features end-to-end for Seattle-area brokerages. Python + FastAPI + Claude/OpenAI + XGBoost + Supabase.
Job Description
About the role Globixs is hiring an AI/ML Engineer to own model development and agent orchestration inside our Real Estate product line. You'll work directly with the AI Architect on the next phase of the platform: expanding our XGBoost-based Automated Valuation Model (currently R² = 0.95), shipping the Property Intelligence Module to paying brokerages, and integrating live MLS and Zillow data. This is a builder role. You'll ship to production, not prototype in notebooks. What you'll do - Own and improve the AVM pipeline (XGBoost today; open to LightGBM, CatBoost, or neural approaches where they win) - Build and extend our multi-agent property intelligence system (PropertySearchAgent, MarketAnalysisAgent, PropertyValuationAgent) using the Claude and OpenAI APIs - Integrate third-party data sources — RapidAPI Zillow, MLS feeds, county assessor data, OpenCage, US Census — into clean, versioned feature pipelines - Design prompts, tool definitions, and orchestration logic for agents running on FastAPI + Supabase + Railway - Ship features end-to-end: data ingestion → model → API → the realtor-facing dashboard - Monitor model drift, evaluate agent outputs, and build eval harnesses for LLM-driven components - Collaborate with frontend engineers on Next.js integrations and with the founder on customer-driven priorities Tech stack Python
FastAPI
XGBoost
Supabase (Postgres)
Claude API (Haiku + Sonnet)
OpenAI
Make.com
n8n
Railway
GCP
Next.js / Streamlit
GitHub Actions How to apply Send to [email protected]: 1. Resume or LinkedIn 2. A link to something you've shipped (GitHub, live demo, or write-up) 3. One paragraph: what would you change about a typical Zillow Zestimate, and why? We review on a rolling basis and reply to every applicant who answers #3.
Minimum Qualifications
2–5 years building ML systems in production (not just notebooks)
Strong Python; comfortable with FastAPI, Pandas, scikit-learn, and a gradient-boosting framework (XGBoost or LightGBM)
Hands-on experience with LLM APIs (Anthropic Claude and/or OpenAI) — prompt design, tool/function calling, structured outputs
Experience with at least one multi-agent framework or custom orchestration pattern (LangGraph, CrewAI, OpenAI Agents SDK, or hand-rolled)
Solid SQL and Postgres; familiar with Supabase or similar BaaS
Git-based workflows, CI/CD (GitHub Actions), and cloud deploys (Railway, GCP, Vercel, or AWS)
Ability to read a product spec, ask the right questions, and ship
Nice to have: real estate / proptech domain experience (MLS, AVM, RETS, comp analysis)
Nice to have: geospatial work (PostGIS, H3, shapely, OSM)
Nice to have: Streamlit or React for demo-ing models to non-technical users
Nice to have: LLM evals / observability (Langfuse, Braintrust, or home-grown)
Preferred Qualifications
Client-facing delivery and cross-functional collaboration experience.
Strong communication and stakeholder management skills.
Experience owning end-to-end delivery outcomes.
Job Snapshot
Role AI/ML Engineer
Location Bothell, WA (Hybrid) or Remote (US)
Employment Type Full-time
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