Staff Machine Learning Engineer I, Search Retrieval

etsy; United States; On-site; USD 190,000 - 230,000; Full time

Job summary

Etsy is seeking a Staff Machine Learning Engineer I to join the Search Retrieval team. You will own end-to-end retrieval systems, combining lexical and semantic techniques to surface relevant listings from a massive catalog.

You will lead cross-functional collaborations, apply state-of-the-art ML/NLP, and deliver production-grade models with measurable impact at Etsy scale.

Qualifications

• Hands-on experience building retrieval or search systems end-to-end.
• Proven track record of delivering impactful ML and NLP solutions across the full pipeline.
• Experience designing scalable ML systems accounting for localization and regional variation.
• Demonstrated technical leadership on complex ML systems and cross-team initiatives.

Responsibilities

• Architect and scale advanced retrieval systems for production use.
• Lead cross-functional collaborations to drive product impact.
• Take retrieval techniques from research into reliable, production-grade systems.
• Design and analyze complex A/B experiments for model quality and latency.
• Investigate and resolve nuanced retrieval behavior issues to improve recall and diversity.
• Define roadmaps with product and engineering leadership for immediate and long-term goals.
• Mentor engineers and scientists, influencing Etsy's search direction.

Skills

Retrieval systems

End-to-end ML

Cross-functional leadership

Technical leadership

NLP solutions

Tools

Dual-encoder models

Vector similarity search

Query expansion

Job description

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 employee, you will tackle unique, meaningful, and large-scale problems alongside passionate coworkers, all the while making a rewarding impact and Keeping Commerce Human.

We believe exceptional companies are built by exceptional teams, and we're intentional about it. That means hiring great people, setting them up for success from day one, and giving them real reasons to grow their careers here. We invest in development that goes beyond promotions, and we foster the trust and relationships that help people do their best work together.

What's the role?

We're looking for a Staff Machine Learning Engineer I to join the Search Retrieval team at Etsy. Our mission is to build efficient, scalable, and intelligent retrieval systems that surface the most relevant listings from a catalog of over a hundred million unique and creative items. We combine lexical matching, semantic retrieval and hybrid models to power the first step in Etsy's search stack, which helps buyers discover items they'll love.

In this role, you'll stay on top of cutting‑edge research in information retrieval and machine learning, and apply the best ideas in production to solve real‑world challenges. You'll collaborate with a cross‑functional team of engineers, applied scientists, and product managers to deliver robust systems and models, and evaluate them through live A/B experiments on Etsy.com .You'll own models end‑to‑end - from data and feature pipelines through training, evaluation, and production serving - and you'll be responsible for the systems that keep them running at Etsy scale. If you're excited about using modern ML to improve search experiences and connect people with meaningful, one‑of‑a‑kind finds, we'd love to hear from you.

This is a full‑time position in Search Retrieval team, reporting to its Engineering Manager.

What's this team like at Etsy?

We apply cutting‑edge machine learning, deep learning, and information retrieval techniques to solve high‑impact problems at Etsy scale. You'll work on challenges such as:

• Designing and improving retrieval engines that power Etsy Search, incorporating techniques like dual‑encoder models, vector similarity search, and query expansion
• Building large‑scale indexing and serving systems for lexical and semantic retrieval
• Collaborating with applied scientists and engineers to bring retrieval models to production, optimize latency and throughput, and scale up across Etsy's catalog
• Conducting offline and online experiments to evaluate model quality, latency, and buyer impact

What does the day‑to‑day look like?

Architect and scale advanced retrieval systems that optimize relevance, recall, latency, and resilience in production.

Lead cross‑functional collaborations to shape and prioritize initiatives that directly drive product impact and strategic goals.

Take retrieval techniques from research and prototypes into reliable, production‑grade systems, owning the full path from experimentation to launch.

Design and analyze complex A/B experiments, setting a high bar for methodological rigor and measurable relevance improvements.

Investigate and resolve nuanced issues in retrieval behavior, leading efforts to enhance candidate recall, coverage, and diversity across user experiences.

Partner closely with product and engineering leadership to define and deliver roadmaps spanning immediate priorities and long‑range initiatives (6-12 months+).

Act as a technical thought leader in retrieval, mentoring engineers and scientists, and influencing the broader direction of Etsy's search systems.

As with any high‑impact role, flexibility is key. Responsibilities may evolve over time in response to business needs and opportunities.

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:

• Hands‑on experience building retrieval or search systems end‑to‑end, including some combination of lexical matching, semantic/embedding‑based retrieval, indexing, and low‑latency serving, and taking them from prototype to production.
• Proven track record of delivering impactful machine learning and NLP solutions across the full pipeline: from data extraction and feature engineering to model development, evaluation, and seamless production integration.
• Experience designing scalable and extensible ML systems that account for localization and regional variation, enabling global product impact.
• Demonstrated technical leadership on complex ML systems, setting technical direction, driving cross‑team initiatives, an