Faire is using machine learning and AI to change wholesale and help local retailers compete with Amazon and big box stores. Our experienced team of engineers and data scientists are developing solutions related to discovery, ranking, search, and recommendations - all with the goal of helping local retail thrive.
Requirements
- 8+ years of industry experience building and scaling distributed systems, with strong fundamentals in distributed infra.
- 5+ years working on search, ranking, or query understanding systems at scale.
- Hands-on experience with traditional, semantic, and hybrid search frameworks (e.g. Elasticsearch, Lucene, Solr, FAISS, Vespa, Weaviate, Milvus).
- Expertise in search indexing, retrieval, and ranking pipelines, including query rewriting, personalization, embeddings, and vector search.
- Experience with ML-driven search systems, including personalization, re-ranking, and reinforcement learning.
- Strong knowledge of latency optimization and building low-latency, high-throughput serving systems.
- Familiarity with AI/ML infra such as model serving (e.g. TensorFlow Serving, TorchServe, Ray Serve), feature stores, and online experimentation.
Responsibilities
- Build and optimize the next-generation Discovery Search and AI stack, integrating LLMs, semantic search, dense vector retrieval, embeddings, and reinforcement learning to serve personalized results with <100ms latency.
- Lead the design and productionization of natural language search and intelligent discovery systems, enabling AI agents to generate relevant collections, explain results, and support retailers in browsing, filtering, and evaluation.
- Tackle deep technical challenges in query understanding, retrieval efficiency, and multi-stage ranking pipelines.
- Develop infrastructure to support state-of-the-art search algorithms while optimizing for cost, speed, and accuracy at scale.
- Shape the technical strategy for how applied AI is leveraged across search and discovery at Faire.
- Collaborate with Data Scientists, Product Managers, and ML Engineers to translate business needs into scalable technical solutions.
- Build and scale the next generation of Search and AI infrastructure at Faire.
Other
- Excellent communication skills and a proven track record of technical leadership and mentorship.
- Hybrid Faire employees currently go into the office 2 days per week on Tuesdays and Thursdays. Effective starting in January 2026, employees will be expected to go into the office on a third flex day of their choosing (Monday, Wednesday, or Friday).
- Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year.
- New York & San Francisco: The pay range for this role is $268,000 - $368,5000
- This role will also be eligible for equity and benefits.
