Staff Applied Scientist II, Search Ranking

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 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:

What’s the role?

As a Staff Applied Scientist II on Etsy’s Search Ranking Team, you will play a pivotal role in developing and optimizing algorithms that determine the relevance and ranking of listings in our search engine. You will leverage advanced machine learning techniques to analyze user behavior, item attributes, and contextual data to ensure that buyers find the most relevant products and have delightful shopping experience. This role involves collaborating closely with fellow applied scientists, machine learning engineers, product managers, and analytics partners to drive data-driven decisions and implement scalable solutions that enhance the search experience.

This is a full-time position reporting to the Engineering Manager. 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?

Search Ranking Team is a dynamic and collaborative group of passionate individuals dedicated to improving how buyers discover unique items on Etsy. We own the systems that power Etsy Search Ranking—responsible for how listings are ranked, evaluated, and optimized across the marketplace. Our responsibilities include:

• Designing, building and maintaining the ranking systems that power Etsy Search operating at massive scale across diverse buyer intents.

• Evolving ranking stacks using state-of-the-art ML models, including neural architectures, learn to rank models, representation learning, natural language understanding, and multimodal modeling, to drive more personalized and relevant search results.

• Applying multi-objective optimization to balance key business and user outcomes such as relevance, engagement, seller diversity, and long-term marketplace health.

• Monitoring marketplace signals to ensure search innovations align with Etsy’s mission and support sustainable growth.

What does the day-to-day look like?

• You will conduct applied ML research to leverage the latest advancements to innovate and improve Etsy’s search system.

• You will prototype, optimize, and productionize scalable ML models in the production framework.

• You will design and execute both offline evaluations and online A/B experiments to ensure model effectiveness and impact.

• You will work with cross-functional teams and partner with product and stakeholders to prioritize and lead projects that align technical solutions with company goals and product objectives.

• You will mentor and support junior team members to help them produce high-quality machine learning solutions.

• 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:

• Deep ML Expertise: Significant industry experience in Applied Science or Machine Learning, with a proven track record of delivering impactful solutions in eCommerce or in related areas such as search, recommendation, or advertising.

• Search & Ranking Specialization: Proven success designing, implementing, and optimizing large-scale systems using techniques such as learning-to-rank (LTR), representation learning, and relevance optimization modeling.

• Production-ready ML Engineering: Strong hands-on experience deploying ML models at scale, including model serving, monitoring, end-to-end feature development and experimentation pipelines.

• Collaboration & Technical Leadership: Track record of driving cross-functional projects, mentoring junior team members, and aligning technical work with strategic product goals.