Staff Product Manager, Search Algorithms

Bachelor’s degree or equivalent experience.

You have 7+ years of experience in product at a high-growth tech startup or as a startup founder with experience working on complex Search systems

You have experience building high-scale products through state-of-the-art engineering and data science

You regularly use ML/AI to solve business problems and are well-versed with recent advancements in the field.

You’re an extraordinarily fast learner. You have the natural curiosity and intellectual horsepower to deeply understand new topics and pick up new skills in a very short time.

You are relentlessly resourceful. When something needs to get done, you always find a way to make it happen. Even when the work is hard, you power through it and execute with limited information and ambiguity.

San Francisco, CA: The pay range for this role is $215,500 - 296,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors, including transferable skills, work experience, market demand, 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 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday).

Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.

Why you’ll love working at Faire

We are entrepreneurs:

The Discovery pillar’s core mission is to make it easy and delightful for retailers to find brands and products their customers will love. This role will own product development of our algorithms powering search, the largest discovery surface by order volume.

Develop and execute on a strategy that takes our search algorithms to the next level

Refine our breakdown of key search query segments, identify novel opportunities for improvements, and diagnose root causes for today’s failure modes

Refine our suite of offline and online metrics to help us better understand the retailer’s search experience and the performance of each component of our search system

Evaluate tradeoffs between technical solutions across velocity, scale, cost, and modularity