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Faire operates a two-sided wholesale marketplace with a tech stack optimized for ML and real-time personalization: PyTorch, Faiss, ScaNN, Pinecone, BERT, and LLM integrations (ChatGPT, Gemini) sit atop Databricks + Spark + Delta Lake. The hiring mix tilts heavily toward engineering and data roles—matching active projects around ML platform architecture, search/discovery, and AI-assisted personalization—while adopting Unity Catalog and scaling toward millions of users. Internal pain points cluster around ML platform performance, data science velocity, and monetization model evolution.
Tech Stack 70 technologies
Core StackKotlin Java JUnit Hibernate MySQL CockroachDB AWS Python PyTorch Pinecone Databricks Apache Spark Delta Lake MLflow Terraform GitHub Actions NetSuite Excel SQL Guice Jersey JSON Protocol Buffers Faiss ScaNN Triton BERT ChatGPT Gemini IAM+39 more
What Faire Is Building
◆Challenges
- Evolving monetization model
- Scaling bd function
- Improving brand quality
- Unlock data science velocity
- Scaling to millions of users
- Operational gaps
- Scaling ml platform
- Scaling marketplace operations
- Improving marketplace economic efficiency
- Optimize ml platform performance
▲Active Projects
- Scalable ml workflows
- Brand acquisition tests
- Ml platform architecture
- Sox compliance
- Monetization model evolution
- Next generation search and discovery experiences
- Enterprise sales motion refinement
- New product extensions
- Ai-assisted search and personalization
- Sales playbook evolution
Hiring Activity
140 roles · 80 in 30d
Department
Seniority
Notable leadership hires: Marketing Analytics Lead, Strategy Analytics Lead, Head of Tax
Company intelligence
