AI/ML Engineer

Globixs; Bothell (WA); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Globixs is hiring an AI/ML Engineer to own model development and agent orchestration inside our Real Estate product line. You’ll ship features end-to-end, from data ingestion to production APIs and realtor-facing dashboards, collaborating with frontend engineers on Next.js integrations.

You’ll work with Python, FastAPI, Claude/OpenAI, and XGBoost to extend an AVM model and build multi-agent property intelligence systems. A strong track record delivering ML systems in production is required.

Qualifications

• 2–5 years building ML systems in production.
• Strong Python; comfortable with FastAPI, Pandas, scikit-learn, and a gradient-boosting framework.
• Hands-on experience with LLM APIs and multi-agent frameworks.

Responsibilities

• Own and improve the AVM pipeline (XGBoost today).
• Build and extend the multi-agent property intelligence system.
• Integrate third-party data sources into clean, versioned feature pipelines.
• Design prompts, tool definitions, and orchestration logic for agents.
• Ship features end-to-end: data ingestion → model → API → realtor dashboard.
• Monitor model drift, evaluate agent outputs, and build eval harnesses.

Skills

Python

FastAPI

Pandas

scikit-learn

XGBoost

LightGBM

LLM APIs

SQL

Postgres

Git & CI/CD

Cloud deployment

Tools

Supabase

Claude API

OpenAI

Railway

GCP

Vercel

Next.js

Streamlit

n8n

Make.com

Job description

Open Role
AI/ML Engineer
Bothell, WA (Hybrid) or Remote (US)

• Full-time

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

Tech stack

• FastAPI
• XGBoost
• Supabase (Postgres)
• Claude API (Haiku + Sonnet)
• OpenAI
• Make.com
• n8n
• Railway
• GCP
• Next.js / Streamlit

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