Director of Applied AI/ML Science

About the role

Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we are using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. The Ads Data team is entering a period of hypergrowth, and the Director of Applied AI/ML Science will own the end-to-end data vision and strategy for the Ads business. This role encompasses the applied science and machine learning powering our marketplace as well as the data foundation underneath it. You will lead and grow a team spanning Applied Scientists and Analytics/Data Engineers while setting the technical vision and roadmap for the group. You will partner closely with cross-functional leaders in Product, Engineering, Design, and Strategy & Analytics to define how the Ads org operates. This is a rare opportunity to shape, from an early stage, the technical and organizational backbone of one of Faire's most important growth engines.

Key facts

What you'll do

Define the holistic data vision and strategy for Ads, spanning retrieval and ranking ML for search ads relevance, query understanding, and personalization, as well as bidding, marketplace, and auction systems including auction design, bid optimization, pacing, budget allocation, and advertiser ROI.

People-manage and grow the full group of Applied Scientists and Analytics Engineers on the Ads Data team, including hiring, mentoring, setting career development paths, and building a strong technical culture as the team scales through hypergrowth.

Own the team's long-term technical roadmap, ensuring it is tightly aligned to company and Ads org strategy, and translate that roadmap into clear priorities, staffing plans, and execution milestones.

Partner with cross-functional leaders to design and run the team's operating model, including planning cadence, prioritization frameworks, roadmap reviews, and cross-team rituals so that Ads Data operates as a high-leverage, well-run function as it scales.

Drive significant business impact through hands-on contribution to high-priority ML and algorithmic problems when needed, while building the team's ability to deliver this work independently and at scale over time.

Serve as a key member of the broader Data leadership team, contributing to how the data organization is built and run, both technically through architecture, tooling, and standards, and organizationally through processes, career frameworks, and hiring practices.

Represent Ads Data in company-level strategic conversations, ensuring data and machine learning considerations are embedded early in product and business planning across Faire.

Establish rigorous evaluation methodologies for Ads ML systems, defining success metrics, monitoring frameworks, and experimentation practices to guide continuous improvement.

Champion data quality, reproducibility, and operational reliability across the Ads stack, from raw event streams through production model serving and post-campaign analysis.

Requirements

8+ years of experience in data science, applied ML, or ML engineering roles, ideally with exposure to ads, search, recommendation systems, marketplaces, or auctions.

4+ years of experience managing technical teams of 5+ people, including senior individual contributors.

Direct experience with ads marketplaces, auction systems, or search and recommendation systems in production environments.

Demonstrated ability to set technical vision and strategy for a team or organization, and to translate that vision into roadmaps, priorities, and measurable outcomes.

Comfort operating across a broad technical surface area, from ML modeling for bidding, auction, ranking, and relevance to data engineering and analytics infrastructure, with enough depth to earn credibility with individual contributors across all these domains.

Strong track record of partnering with cross-functional partners to define team operating models and drive cross-functional execution at scale.

Excellent written and verbal communication skills, with experience presenting complex technical concepts to both technical and non-technical audiences.

A proven commitment to maintaining high standards for code quality, data integrity, and model performance in production systems.

Nice to have

Experience building and scaling data platforms and ML infrastructure in cloud environments.

Background working with large-scale behavioral event data and real-time data pipelines.

Experience with experimentation frameworks and causal inference methods for measuring marketing impact.

Familiarity with retail or wholesale commerce domains and advertiser-facing products.

Practical notes

This role is based in San Francisco, California, and requires in-office work.

Employment is full-time, and the work location is fixed in San Francisco, with no remote options specified.

There are no specified deadlines for application submission in the provided source materials.