Machine Learning Engineer II, Search Ranking

Key Skills

Apache Beam, Design, Google Cloud Platform (GCP), Kubeflow, Large Language Models - LLMs, Machine learning techniques, PyTorch, SPARK Programming, TensorFlow

Job Description

We are looking for a Machine Learning Engineer II in Search Ranking team to understand buyer shopping missions, personalize content, and rank the most relevant search results to our buyers on search pages.

As a Machine Learning Engineer, you will work closely with applied scientist to build custom large-scale machine-learning models powered in production to deliver customer impact. We are individuals who are data driven, and are passionate about making ML innovations in areas such as: Learning-To-Rank, Natural Language Processing, LLM, Reinforcement Learning to improve the Etsy search experience!

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 are a team of applied scientists, ML engineers, data analysts, and product managers, who work as a multi-functional team to build, improve and maintain online search ranking systems that can drive customer impact in Etsy.

• We design, develop and maintain of large scale, performant machine learning systems

• We research and implement novel ML models to improve relevance and personalization in search results

• We influence product roadmap using data backed analysis

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

• 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.

• 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 joy in continuous learning and self-improvement. You care about how ML impacts real people. It also helps if you have:

• 1+ years of experience in areas related to Search, Recommendation Systems, Personalization, and Applied ML.

• Proficiency in writing high quality production code, demonstrating strong software engineering 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 and passion 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 a strong Slack and Google Docs.

• Self-directed, flexible, and strong sense of ownership.

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.