2 months ago
Base Salary
$200k - $275k/yr
Responsibilities
- Own the next-generation search engine, integrating LLMs, query understanding, dense vector retrieval, personalization embeddings, multi-stage ranking, and reinforcement learning for sub-100ms personalized product feeds.
- Design and productionize natural-language search and discovery systems, including intelligent agents that generate collections, explain search results, and assist with browsing, filtering, and evaluation.
- Lead model development and GPU-based deployment using frameworks such as Triton.
- Mentor senior Applied Scientists and machine-learning engineers and establish best practices for model development, agent-workflow evaluation, and MLOps.
Requirements
- 7+ years of experience building large-scale machine-learning systems, including 3+ years in search, recommendation, or ads ranking.
- Hands-on experience with deep-learning libraries such as PyTorch and vector-search infrastructure such as Faiss, ScaNN, or Pinecone.
- Experience productionizing models that combine LLMs such as BERT or GPT-class models with structured features for personalization.
- Strong Python skills and experience operating reliable systems in high-stakes environments.
- Excellent communication and cross-functional influence.
- Contributions to open-source ML libraries or peer-reviewed ML/AI publications are preferred.
- An MS or PhD in Computer Science, Statistics, or a related STEM field is preferred.
- Strong model-development, agent-workflow evaluation, and MLOps practices are preferred.
Benefits
- Eligible for equity and comprehensive benefits.
- Hybrid employees work in the office 3 days per week on Tuesdays, Thursdays, and one flex day on Monday, Wednesday, or Friday.
- Hybrid employees may work remotely for up to 4 weeks per year.
- Access to enterprise AI tools and a growth-oriented workplace.
- Equal employment opportunities and reasonable accommodations are provided.
Categories
About Faire
Faire is a wholesale technology platform empowering brands and retailers to strengthen the unique character of local communities.