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Staff Applied Scientist I

  • Hybrid
  • Brooklyn
  • Full-time

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:

$218,000.00 - $257,000.00

What’s the role?

As a Staff Applied Scientist, you will be responsible for initiating and delivering new solutions for the domain application of Recommendations. We are looking for individuals who are product & technology driven, and are passionate about making deep learning innovations in areas such as: Natural Language Processing, Representation Learning, Clustering, Optimization,  Graph Learning, and Reinforcement Learning to help improve the Etsy buyer/seller 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?

The Retrieval team builds capabilities to select relevant item-candidates to help product teams to provide personalized user experiences. We use machine learning algorithms to train models which can be used to choose relevant personalized candidate-sets for our recommendation engine. We are looking for an experienced machine learning scientist who can help build Etsy’s next generation capabilities for the candidate generation.
  

What does the day-to-day look like?

  • Develop models with custom architecture or objective functions that target Etsy-specific problems.

  • Stay current with research: Read cutting-edge ML and AI papers and bring innovative, impactful techniques to solve real-world problems.  

  • Productionize ML solutions: Develop robust systems for training, deploying, and monitoring ML models at scale.  

  • Mentor other applied scientists and guide them during their projects.  

  • Collaborate cross-functionally: Work closely with software engineers, data scientists, product managers, and designers.  

  • 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:

  • Proven ability to drive projects forward: You can effectively identify and implement solutions, balance risk and speed, and adapt your approach as needed to deliver results.

  • Successful track record of applying deep learning machine learning techniques in addressing real-world problems and looking for opportunities to make impacts.

  • Extensive experience with machine learning and deep learning solutions across the entire machine learning stack, from data collection to evaluation.

  • Ability to take on and lead unconstrained problems and know when to seek help and how to deliver.

  • Ability to write and manipulate data at a large scale, in a distributed environment.

  • Strong coding skills: You write robust, production-quality code (Python, Scala, Java, or equivalent). You’re experienced with tools like Spark, GCP, and Airflow. 

  • You earnestly enjoy coding and love to raise the bar on engineering standards by championing best practices, clean code, and robust testing.  

  • Collaboration and communication: You can articulate complex concepts to both technical and non-technical audiences.  

  • 5+ years of applied science machine learning.

  • Advanced degree in ML or related field: Preferred but not required. We recognize relevant industry experience can be just as valuable.  

  • Experience in cloud computing (for example Google Cloud Platform).  

  • Experience in representation learning.

  • Experience in Approximate-Nearest-Neighbor (ANN) search preferred but not required.

  • Experience in building production search, recommendations, advertising, knowledge base (structured data), or general e-commerce systems.  

  • Experience using the following frameworks: Spark, Airflow, Kubeflow, Tensorflow or PyTorch.

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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