Senior Applied Scientist I, Search Relevance

Company Description
Etsy is the global marketplace for unique and creative goods. We build, power, and evolve the tools and technologies that connect millions of entrepreneurs with millions of buyers around the world. As an Etsy Inc. employee, whether a team member of Etsy, Reverb, or Depop, you will tackle unique, meaningful, and large-scale problems alongside passionate coworkers, all the while making a rewarding impact and Keeping Commerce Human.

Salary Range:

$164,000.00 - $192,000.00

What’s the role?

We are looking for a Senior Applied Scientist I, Search Relevance to join the Search team at Etsy. We develop efficient, state-of-the-art, large-scale search models that sift through a universe of over a hundred million special, extraordinary items to help Etsy buyers find something they will love.

In this team, you'll closely follow the latest research and implement its best ideas efficiently, at scale for the benefit of Etsy's buyers. Working hands-on with a cross-disciplinary team, you will deliver robust production models that will be A/B tested live on Etsy.com! Does helping people find the perfect handmade or vintage good from using the latest ML research sound exciting to you? If so, we could be the perfect match.

This is a full-time position in Search Relevance initiative. In addition to salary, you will also be eligible for an equity package, an annual performance bonus, and our competitive benefits that support you and your family as part of your total rewards package at Etsy.

For this role, we are considering candidates based in the United States. Candidates living within commutable distance of Etsy’s Brooklyn Office Hub or in the San Francisco Bay Area may be the first to be considered. For candidates within commutable distance, Etsy requires in-office attendance once or twice per week depending on your proximity to the office. Etsy offers different work modes to meet the variety of needs and preferences of our team. Learn more details about our work modes and workplace safety policies here.

What’s this team like at Etsy?

The Search Relevance initiative is a ML team that strives to improve the relevancy of search results for Etsy buyers. We apply the latest techniques from machine learning, natural language processing, and information retrieval research at Etsy’s scale. Here is a taste of some of the problems we are solving:

• Use the latest in machine learning and information retrieval to improve our search pipelines

• Use concepts like graph neural networks, random walk based graph recommendation engine, deep neural dense retrieval models powered by Transformers etc to advance the state of the search retrieval pipeline

• Work closely with fellow ML engineers, full-stack engineers, applied scientists, and product managers, in cross-functional teams develop & test large scale experiments

• Optimize ML models to meet latency SLAs at the scale of Etsy production traffic and launch live A/B experiments to test our hypotheses.

What does the day-to-day look like?

• You will work in a cross-functional team to prioritize projects which help achieve our product targets.

• You will build, deploy, test and maintain scalable machine learning models by applying the latest concepts in research and industry.

• You will run various A/B experiments to improve search relevance.

• You will work work closely with our product manager to help build roadmaps which range between a few weeks to 6-12 months

• Of course, this is just a sample of the kinds of work this role will require! You should assume that your role will encompass other tasks, too, and that your job duties and responsibilities may change from time to time at Etsy's discretion, or otherwise applicable with local law.

Qualities that will help you thrive in this role are:

• You have experience developing impactful solutions to machine learning & NLP problems involving some or all of the following parts of the pipeline: data extraction, developing and training machine learning models, working the new model into production applications.

• You have experience building scalable solutions ta