Company DescriptionEtsy 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 are looking for a passionate and talented Senior Machine Learning Engineert to join our Recommendation Ranking team. Our team develops Machine Learning models to understand buyers, personalize, and rank recommendations across Etsy.com and the Etsy app. As an Applied Scientist, you will work closely with Software Engineers to improve the shopping experience for 90+ million buyers. We are looking for individuals who are product & technology driven, and are passionate about making ML innovations in areas such as: Ranking, Reinforcement Learning, LLM and Deep Learning!
This is a full-time position reporting to the Engineering Manager.
What does the day-to-day look like?- Work closely with software engineers, data scientists, product managers, and designers to set the future technical direction of Etsy's recommendation system
- Push the state of the art and apply the latest advances in ML to improve buyer and seller experiences on Etsy such as:
- Build user models that allow us to better understand the unique interests, tastes, and shopping mission of Etsy's buyers.
- Develop models that target Etsy-specific problems, including but not limited to personalized ranking, multi-objective optimization, diversity constraints etc.
- Design foresight and intent prediction models that anticipate future buyer needs, predict lifecycle transitions.
- Improve feed reactivity and freshness, ensuring recommendations adapt quickly to user actions, emerging trends and seasonal shifts.
- Prototype, optimize, and productionize large-scale ML models that help deliver key results
- Conduct experiments (A/B testing etc.) to validate the effectiveness of ML models and pipelines
- 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 a successful track record of applying machine learning techniques in addressing real-world problems.
- You have experience with / working in one of the following fields: deep learning, multi-modal learning, reinforcement learning etc.
- You have hands-on experience in training, deploying, monitoring, debugging and iterating on production machine learning systems in search, recommendation, and/or ads systems.
- You have production experience developing large-scale machine learning systems in Python, Scala, PyTorch, TensorFlow or similar languages.
- You write understandable and testable code. You have the ability to write and manipulate data at a large scale and you have an eye towards maintainability.
- An M.S. or Ph.D. degree in Computer Science or related engineering fields with at least two years of practical machine learning experience
Compensation & BenefitsIn addition to salary, you'll be eligible for an equity package, an annual performance bonus, and our competitive benefits that support you and your family. Base salary is determined by your location, skills, and experience.
Etsy uses two geographic pay zones to reflect the labor markets where we compete for talent: one called Geo-1, covering the New York City metropolitan area, San Francisco Bay Area, and Seattle metropolitan area, and one called Geo-2, covering all other U.S. locations. Salary ranges for this role vary by zone and are listed below.
LocationWe prioritize candidates based within commutable distance of Etsy's Brooklyn Office. Depending on proximity, we ask team members to come in once or twice per week. Remote candidates outside commutable distance may be considered on a case-by-case basis, with the expectation of occasional travel to the office. Learn more details about our work modes and workplace safety policies here.
Salary Range: Geo-1: 182,000.00 - 246,000.00 USD Annual Geo-2: 164,000.00 - 222,000.00 USD Annual
What's NextIf 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 PromiseAt 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 and is committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, national origin, religion or creed, sex, pregnancy (including childbirth and related medical conditions), gender, gender identity or expression, sexual orientation, age, citizenship or immigration status, marital or familial status, physical or mental disability, medical condition, genetic information, military or veteran status**, or any other characteristic protected by applicable federal, state, or local law**. If, due to a disability, you need an accommodation during any part of the interview or hiring process, please let your recruiter know and we will work with you to meet your needs. While Etsy supports visa sponsorship, sponsorship opportunities may be limited to certain roles and skills.
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