Filtr uses AI to scan 1000+ jobs and finds postings that perfectly matches your resume

Faire is looking to solve the problem of helping independent retailers compete with large e-commerce giants by leveraging technology, data, and machine learning to connect them with the best products from around the world.

Requirements

• 1-3 years of industry or research experience using machine learning to solve real-world problems, ideally including work in search, recommendations, or ads ranking.
• Hands-on experience with deep-learning libraries (e.g., PyTorch) and vector-search infrastructure (e.g., Faiss, ScaNN, Pinecone).
• A strong track record of productionizing models that blend LLMs (e.g., BERT, GPT-class) with structured features to drive personalization.
• Strong Python skills, deep respect for system reliability and ownership, and experience operating in high-stakes environments.
• Contributions to open-source ML libraries or peer-reviewed publications in ML/AI.
• MS or PhD in Computer Science, Statistics, or a related STEM field.

Responsibilities

• Contribute to the next-generation Search engine, integrating LLMs, query understanding, dense vector retrieval, deep personalization embeddings, multi-stage ranking, and reinforcement learning to serve personalized product feeds with <100 ms latency.
• Design and productionize natural-language search and discovery systems, enabling intelligent agents to generate relevant and personalized collections, explain search results, and assist retailers in browsing, filtering, and evaluation.
• Collaborate on model development and GPU-based deployment efforts, leveraging frameworks like Triton to scale inference reliably and efficiently.

Other

• Excellent communication and cross-functional influence—you raise the technical bar beyond your immediate team.
• A product-focused mindset and a bias toward execution—you move quickly from paper to prototype to production.
• We are entrepreneurs: Faire is being built for entrepreneurs, by entrepreneurs.
• Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.
• 2 days per week in-office attendance on Tuesdays and Thursdays, with flexibility to work remotely up to 4 weeks per year.