Senior Data Scientist II, Search

Brooklyn, NY, United States

Etsy

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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:

$205,000.00 - $237,000.00

What’s the role?

Etsy’s Search Retrieval team is hiring a Senior Applied Scientist II to help us connect millions of buyers to the right listings across our unique marketplace. Our team is responsible for the first step in the search stack, retrieving a high-quality set of relevant candidates, by operating and evolving a diverse set of retrieval systems, including lexical retrieval engines (e.g., BM25), embedding-based retrieval, and hybrid approaches.


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?

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 like:

  • Designing and improving retrieval systems 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?

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

  • You will build and deploy scalable retrieval systems that balance relevance, recall, and performance

  • You will drive innovation by bringing in state-of-the-art retrieval algorithms

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

  • You will analyze model performance, debug issues in retrieval behavior, and lead efforts to improve the candidate recall and diversity in search results

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

  • You will mentor other engineers and help shape the technical direction of retrieval at Etsy

  • 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 taking into account localization specific needs to cater to global customer needs. 

  • You have strong engineering and coding skills, with the ability to write high quality production code. Proficiency in Python, Scala, Java and/or other equivalent languages. 

  • You have experience working with machine learning frameworks & technologies such as Tensorflow/TFX, PyTorch, Kubeflow.

  • You turn ideas into deeply reliable and well tested code that other people – or you, six months into the future – will find easy to comprehend and modify.

  • You are a mindful, empathetic, and communicative member of your team.

  • Continuous and recent experience of pushing production level Machine Learning code  


 

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.

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Category: Data Science Jobs

Tags: A/B testing Deep Learning Engineering Java Kubeflow Machine Learning ML models NLP Python PyTorch Scala TensorFlow TFX

Perks/benefits: Career development Competitive pay Equity / stock options Salary bonus

Region: North America
Country: United States

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