Staff Applied AI/ML Scientist - Search
Confirmed live in the last 24 hours
Faire
Compensation
$224,000 - $308,000/year
Job Description
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.
By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.
About this role
As a Staff Applied AI/ML Scientist on the Search Group, you’ll drive the technical vision, ML algorithm strategy, and system design powering one of the most critical levers for customer value and company growth—Search (think about what you do when you land on any e-commerce site). You’ll lead the advancement of real-time Search and Recommendation systems behind our next-generation shopping experiences.
You’ll operate at the forefront 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/brands for any given query from the users.
This is a rare opportunity to own end-to-end personalization in a high-scale, deeply multi-modal environment—while mentoring a team of talented scientists and engineers.
What you’ll do
- Own 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 <100ms 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.
- Lead model development and GPU-based deployment efforts, leveraging frameworks like Triton to scale inference reliably and efficiently.
Qualifications
- 7+ years of experience building large-scale ML systems, including 3+ 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 track 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—you raise the technical bar beyond your immediate team.
Great to Have
- 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.
Salary Range
California: the pay range for this role is $224,000 to $308,000 per year.
This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as 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.
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