Faire
Senior Applied AI/ML Scientist - Search
Faire, San Francisco, California, United States, 94199
About Faire
Faire is an online wholesale marketplace built on the belief that the future is local — independent retailers around the globe are doing more revenue than Walmart and Amazon combined, but individually, they are small compared to these massive entities. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so that small businesses everywhere can compete with these big box and e-commerce giants.
About This Role As a
Senior Applied AI/ML Scientist
on the Search group, you’ll help shape the technical vision, machine-learning algorithm strategy, and system design behind one of our most important growth levers: Search. You’ll advance real-time Search and Recommendation systems that power next-generation shopping experiences. You’ll work at the frontier of algorithms, combining large language models, natural-language processing, query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products and brands for every user query. This is a rare chance to influence end-to-end personalization in a high-scale, deeply multi-modal environment while collaborating closely with a talented team of scientists and engineers.
What You’ll Do
Contribute to our next-generation Search engine by integrating LLMs, query understanding, dense-vector retrieval, deep personalization embeddings, multi-stage ranking, and reinforcement learning to serve personalized product feeds with sub-100 ms latency.
Design and productionize natural-language search and discovery systems so that intelligent agents can generate relevant and personalized collections, explain search results, and assist retailers with browsing, filtering, and evaluation.
Lead model development and GPU-based deployment efforts, leveraging frameworks like Triton to scale inference reliably and efficiently.
Share best practices around model development, agent-workflow evaluation, and MLOps, and help teammates level up through code reviews and technical guidance.
Qualifications
4+ years of experience building large-scale ML systems, including 2+ years in search, recommendation, or ads ranking.
Hands-on experience with deep-learning libraries (e.g. PyTorch) and vector-search infrastructure (e.g. Faiss, ScaNN, Pinecone).
A strong record of productionizing models that blend LLMs (e.g. BERT, GPT-class) with structured features to drive personalization.
A product-focused mindset and a bias toward execution—you move quickly from paper to prototype to production.
Strong Python skills, deep respect for system reliability and ownership, and experience operating in high-stakes environments.
Excellent communication and cross-functional influence that raise the technical bar beyond your immediate team.
Great To Haves
Contributions to open-source ML libraries or peer-reviewed publications in ML/AI.
Master’s or PhD in Computer Science, Statistics, or a related STEM field.
Salary & Benefits California: the pay range for this role is $192,000 to $264,000 per year. This role will also be eligible for equity and benefits. Actual base pay will be determined based on transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.
Hybrid Faire employees currently go into the office 2 days per week on Tuesdays and Thursdays. Beginning January 2026, employees will be expected to go into the office on a third flex day of their choosing (Monday, Wednesday, or Friday). Hybrid roles may also allow remote work up to 4 weeks per year. Some positions may require onsite attendance 5 days per week as indicated in the job posting.
Why You’ll Love Working at Faire
We are entrepreneurs: Faire is built for entrepreneurs, by entrepreneurs, with a mission to empower entrepreneurs to chase their dreams.
We level the playing field with technology and data to connect brands and boutiques globally, building a community of more than 350,000 small business owners.
We build products our customers love and aim to grow the pie for small businesses.
We are curious and resourceful: we explore possibilities, test assumptions, and reason from first principles using data.
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. Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process; applicants may request accommodations. To request reasonable accommodation, please fill out our Accommodation Request Form (https://bit.ly/faire-form).
Note: This description reflects the core responsibilities and qualifications for the Senior Applied AI/ML Scientist role in the Search group and does not include external job postings or unrelated content.
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About This Role As a
Senior Applied AI/ML Scientist
on the Search group, you’ll help shape the technical vision, machine-learning algorithm strategy, and system design behind one of our most important growth levers: Search. You’ll advance real-time Search and Recommendation systems that power next-generation shopping experiences. You’ll work at the frontier of algorithms, combining large language models, natural-language processing, query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products and brands for every user query. This is a rare chance to influence end-to-end personalization in a high-scale, deeply multi-modal environment while collaborating closely with a talented team of scientists and engineers.
What You’ll Do
Contribute to our next-generation Search engine by integrating LLMs, query understanding, dense-vector retrieval, deep personalization embeddings, multi-stage ranking, and reinforcement learning to serve personalized product feeds with sub-100 ms latency.
Design and productionize natural-language search and discovery systems so that intelligent agents can generate relevant and personalized collections, explain search results, and assist retailers with browsing, filtering, and evaluation.
Lead model development and GPU-based deployment efforts, leveraging frameworks like Triton to scale inference reliably and efficiently.
Share best practices around model development, agent-workflow evaluation, and MLOps, and help teammates level up through code reviews and technical guidance.
Qualifications
4+ years of experience building large-scale ML systems, including 2+ years in search, recommendation, or ads ranking.
Hands-on experience with deep-learning libraries (e.g. PyTorch) and vector-search infrastructure (e.g. Faiss, ScaNN, Pinecone).
A strong record of productionizing models that blend LLMs (e.g. BERT, GPT-class) with structured features to drive personalization.
A product-focused mindset and a bias toward execution—you move quickly from paper to prototype to production.
Strong Python skills, deep respect for system reliability and ownership, and experience operating in high-stakes environments.
Excellent communication and cross-functional influence that raise the technical bar beyond your immediate team.
Great To Haves
Contributions to open-source ML libraries or peer-reviewed publications in ML/AI.
Master’s or PhD in Computer Science, Statistics, or a related STEM field.
Salary & Benefits California: the pay range for this role is $192,000 to $264,000 per year. This role will also be eligible for equity and benefits. Actual base pay will be determined based on transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.
Hybrid Faire employees currently go into the office 2 days per week on Tuesdays and Thursdays. Beginning January 2026, employees will be expected to go into the office on a third flex day of their choosing (Monday, Wednesday, or Friday). Hybrid roles may also allow remote work up to 4 weeks per year. Some positions may require onsite attendance 5 days per week as indicated in the job posting.
Why You’ll Love Working at Faire
We are entrepreneurs: Faire is built for entrepreneurs, by entrepreneurs, with a mission to empower entrepreneurs to chase their dreams.
We level the playing field with technology and data to connect brands and boutiques globally, building a community of more than 350,000 small business owners.
We build products our customers love and aim to grow the pie for small businesses.
We are curious and resourceful: we explore possibilities, test assumptions, and reason from first principles using data.
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. Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process; applicants may request accommodations. To request reasonable accommodation, please fill out our Accommodation Request Form (https://bit.ly/faire-form).
Note: This description reflects the core responsibilities and qualifications for the Senior Applied AI/ML Scientist role in the Search group and does not include external job postings or unrelated content.
#J-18808-Ljbffr