Rental search marketplace matching renters to apartments with ML
Apartment List runs a renter-facing apartment marketplace built on React, Python and GCP, with a deep ML toolkit (scikit-learn, XGBoost, TensorFlow, PyTorch, Airflow) and OpenAI now being adopted. Hiring skews senior and splits between engineering, marketing and data, matching job-post pain points around marketing attribution gaps and a push to rebuild marketing around AI. A Salesforce-NetSuite integration project points to quote-to-cash work on the property-side revenue engine.
Apartment List operates an online rental marketplace that matches renters with curated apartment listings and guides them through the search. The platform covers millions of rental units and also serves the multifamily side through a lister domain and partner integrations. The company is privately held, headquartered in San Francisco, and employs 201–500 people. It hires across the United States, Canada and Israel, with teams spanning engineering, marketing, data, sales, product and support.
Apartment List uses React, JavaScript, Python, GCP, Vercel, Apache Airflow, scikit-learn, XGBoost, TensorFlow, PyTorch, Looker, Tableau, Salesforce, NetSuite, Zendesk, Jira and Iterable, and is adopting OpenAI.
Yes. Engineering is its largest hiring area, followed closely by marketing and data, with most openings at senior level across the United States, Canada and Israel.
Current projects include ML ops infrastructure, the lister domain, partner integrations, a Salesforce-NetSuite integration, ad copy and bidding A/B tests, and an AI and automation roadmap for marketing.
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Apartment List's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.