
Keep commerce human.
Engineering Manager, ML Recommendations at Etsy
About the role
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:
$226,000.00 - $294,000.00
What’s the role?
We are looking for an Engineering Manager to lead the Recommendations Retrieval team at Etsy. This team owns the core retrieval algorithms that power Etsy’s recommendation surfaces, helping buyers discover unique items they’ll love across the homepage, listing pages, cart, and beyond. As we invest in next-generation retrieval capabilities, you’ll guide the team through scaling our candidate generation systems, modernizing our retrieval stack, and integrating machine learning to improve personalization and relevance at scale.
You will lead a talented group of engineers and applied scientists responsible for building and operating the systems that generate high-quality, personalized candidates for Etsy’s recommendation models. This is a high-impact opportunity to shape the foundation of how Etsy connects buyers with the items and sellers they’ll love most.
This is a full-time position reporting to the Director of Engineering, Recommendations. 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 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 Recommendations Retrieval team sits within the Recommendations organization and provides the foundational retrieval layer that powers Etsy’s recommendation experiences across the marketplace. Our mission is to build fast, scalable, and intelligent candidate generation systems that surface the most relevant and personalized items for every buyer at global scale.
This team is responsible for:
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Building personalized discovery experiences by owning the candidate generation and retrieval systems that power Etsy’s homepage feed, listing-page recommendations, and cross-sell surfaces, with a deep focus on understanding individual buyer intent and taste.
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Advancing user understanding and personalization by developing and scaling models that capture buyer behavior, preferences, and context
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Transforming retrieval into a discovery engine by leveraging LLMs and generative AI to move beyond traditional candidate generation enabling serendipitous, intent-aware discovery experiences that surface unexpected and inspiring items for buyers
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Partnering closely with applied scientists, Ranking, ML Platform, and Data Engineering teams to co-develop user understanding models, integrate personalization signals, and bring new discovery experiences to life at scale.
You’ll help define the roadmap for Etsy’s recommendations retrieval systems, balancing operational excellence, developer velocity, and innovation in ML-powered retrieval.
What does the day-to-day look like?
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Lead and grow a team of engineers and applied scientists responsible for designing, building, and maintaining candidate generation and retrieval systems at scale.
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Define and execute the technical strategy for recommendations retrieval, ensuring we balance innovation, reliability, and performance.
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Oversee the evolution of our retrieval infrastructure, ensuring healthy data pipelines, index quality, and system performance across recommendation surfaces.
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Collaborate with cross-functional partners including Ranking, Recs Systems, ML Platform, Data Engineering, Analytics, and Product to shape the direction of the recommendations stack.
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Foster a culture of technical excellence, mentorship, and continuous learning through regular design reviews, code reviews, and structured performance feedback.
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Establish clear technical goals, monitor system health, and proactively identify and resolve performance and reliability bottlenecks.
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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:
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Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related technical field.
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Proven experience in large-scale retrieval, recommendation, or search systems, with a strong background in candidate generation, ANN/vector search, or ML-powered personalization.
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2+ years of experience leading engineering teams, ideally in real-time recommendation, search, or ads systems.
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Familiarity with modern retrieval and ranking techniques, including neural retrieval, two-tower models, and transformer-based embeddings and architectures.
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Experience with system performance optimization, caching strategies, and scaling high-throughput, low-latency services.
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Strong communication and collaboration skills; capable of bridging technical and non-technical stakeholders.
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Track record of driving complex technical projects from conception to launch while maintaining a high bar for quality and reliability.
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Proven people leadership in high-stakes, fast-moving environments, remaining steady and solutions-oriented through shifting priorities and ambiguous direction
Additional Information
What's Next
If you're interested in joining the team at Etsy, please share your resume with us and feel free to include a cover letter if you'd like. As we hope you've seen already, Etsy is a place that values individuality and variety. We don't want you to be like everyone else -- we want you to be like you! So tell us what you're all about.
Our Promise
At Etsy, we believe that a diverse, equitable and inclusive workplace furthers relevance, resilience, and longevity. We encourage people from all backgrounds, ages, abilities, and experiences to apply. Etsy is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status, or any other characteristic protected by applicable law. If, due to a disability, you need an accommodation during any part of the application or interview process, please let your recruiter know. While Etsy supports visa sponsorship, sponsorship opportunities may be limited to certain roles and skills.
Required skills
Engineering management
Distributed systems
Recommendation systems
Machine learning
Personalization
Technical strategy
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About Etsy

Etsy
PublicEtsy, Inc. is an American e-commerce company focused on handmade or vintage items and craft supplies. Its marketplace includes categories such as jewelry, apparel, home decor, furniture, toys, and art. Items described as vintage must be at least 20 years old.
1,001-5,000
Employees
Brooklyn
Headquarters
$3.5B
Valuation
Reviews
10 reviews
4.1
10 reviews
Work-life balance
3.8
Compensation
2.8
Culture
4.2
Career
3.2
Management
2.5
75%
Recommend to a friend
Pros
Flexible hours and remote work options
Great team and collaborative atmosphere
Creative and innovative work environment
Cons
High workload and overwhelming demands
Poor management and lack of direction
Limited career advancement opportunities
Salary Ranges
339 data points
Senior/L5
Senior/L5 · Senior Analytics Manager
1 reports
$229,410
total per year
Base
$199,400
Stock
-
Bonus
-
$229,410
$229,410
Interview experience
1 interviews
Difficulty
4.0
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 0%
Negative 100%
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
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