We are looking for an Applied Machine Learning Scientist in the Marketplace Optimization team to help understand buyer shopping missions, customers’ long term values, seller success, marketplace health and customer interest shift during the online shopping. As an Applied Scientist, you will work closely with software engineers to build custom large-scale machine-learning models powered in production to deliver customer impact. We comprise a team which are driven by data and passionate about innovating in the field of Machine Learning (ML). Our areas of interest and expertise span Ranking, Optimization, Natural Language Processing, Deep Learning, and Reinforcement Learning. Our primary objective is to apply these sophisticated techniques to improve the search experience on our platform.
This is a full-time position reporting to the Engineering Manager of Marketplace Optimization, and the base salary range will be $184,000 - 216,000 USD per year. 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. This role requires your presence in Etsy’s Brooklyn office in an in-person or flex capacity. Candidates living within commutable distance of the Brooklyn Hub, may be the first to be considered. Etsy offers different work modes to meet the variety of needs and preferences of our team. Learn more about our Flex and Office-based work modes and workplace safety policies here.
What’s this team like at Etsy?
The Marketplace Optimization team is a part of the Search group at Etsy, who are committed to refining search ranking quality for both buyers and sellers. We work on the last pass ranking of search results, which significantly shapes the overall customer search experience. The team is an eclectic mix of machine learning engineers, applied scientists, and a product manager. Collaborating intensively with software engineers and various product and enablement teams throughout the organization, we are involved in the creation and execution of advanced machine learning algorithms that consistently facilitate improved search results.
- Design, develop and maintain of large scale, performant machine learning systems
- Research and implement novel ML models to improve buyer shopping missions, customers’ long term values, seller success, marketplace health and customer interest shift in search results
- Work with analysts or independently on the pre-analysis and post-analysis before scoping projects
- Influence product roadmap using data backed analysis
- Mentor junior scientists on the team
What does the day-to-day look like?
- Find opportunities to improve our buyers’ search experience and propose a project plan backed up with data analysis
- Initiate and lead new tracks of work to improve ranking capabilities of Etsy’s Search engine.
- Develop innovative ML ranking models that optimize for various business goals to power search at scale.
- Scope data-driven projects and collaborate with internal & external teammates from Data, Modeling and ML Infrastructure.
- Iterate quickly to design, implement, optimize, and test new modeling improvements in both offline and production A/B experiment settings.
- Draw conclusions from experiment results
- Lead high code quality and engineering standards in the team; Maintain and improve core ML pipeline
- 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 are a caring teammate who enjoys helping others. Your growth mindset means you find happiness in continuous learning and self-improvement. You care about how ML impacts real people. It also helps if you have:
- 3+ years of experience in areas related to Search, Recommendation Systems, Personalization, and Applied ML.
- Proficiency in writing high quality production code, demonstrating strong modeling, data understanding and coding skills
- Proficiency in neural ML frameworks such as Tensorflow, PyTorch
- Experience with web-scale data preprocessing and ML workflow such as Apache Spark, Beam, Kubeflow Pipelines etc
- Experience working with cloud computing services such as Google Cloud Platform
- A product focus for using machine learning to address real-world problems. Knowledge of various machine learning techniques and key parameters that affect their performance
- Strong verbal and written communications skills and comfort working in a remote team with Slack and Google Docs.
- Self-directed, flexible, and strong sense of ownership.
- A previous track record of publications in one of the following fields: information retrieval, recommendation systems, knowledge graphs, natural language processing, reinforcement learning.
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.
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 and is an affirmative action employer. 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. If, due to a disability, you need an accommodation during any part of the interview process, please let your recruiter know. While Etsy supports visa sponsorship, sponsorship opportunities may be limited to certain roles and skills.
For U.S. roles only:
Many Etsy roles are open to remote candidates, and you'll be able to identify which ones within the location header of each job description. We're open to remote hires from all U.S. states except Hawaii and Alaska.