Etsy is looking for a talented and driven Engineering Manager to lead one of the machine learning ranking teams within the Relevance initiative under the Personalization Engine (Perso Engine for short) organization. Perso Engine is an enablement organization that enables over 20+ product engineering teams across Etsy to leverage machine learning in building recommendations, personalization, and discovery products. As a Manager, you will be leading a team of machine learning scientists and engineers and will be directly responsible for driving the development of state-of-the-art models, fostering cross-functional collaborations to align with business objectives, and ensuring a culture of innovation and teamwork.

This is a full-time position. 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 team develops and maintains machine learning ranking and buyer experience optimization models. Examples include, models for ranking queries, reviews, shops, urgency signals, as well as models for optimizing audience targeting to reduce buyer overwhelm and improve user experience. Our goal is to enable ML-driven personalization at scale across Etsy and help support product engineering teams drive several business KPIs.

• In order to serve our customers, we are creative and resourceful, trading off short and long-term solutions strategically.

• We strive to build capabilities that can be used by many different customers and across several platforms and pages.

• We're lifelong learners, experiment relentlessly, and always seek to improve our understanding of the capabilities we build in order to perfect them.

• We are customer centric! We drive impact by leveraging our talent and resources to build the capabilities that our customers need and want the most.

• In order to build impactful, maintainable, scalable, and efficient capabilities, we work closely with platform and infrastructure teams.

What does the day-to-day look like?

• Manage a team of 5-7 machine learning scientists and engineers: hire, manage performance, assign tasks, provide technical guidance, and ensure that projects are completed on time.

• Manage cross-functional relationships with upstream product engineering teams and downstream platform, data, and infrastructure teams.

• Define an engineering roadmap for the team that aligns with the initiative’s strategy to drive innovation, scalability, and efficiency.

• Foster a culture of collaboration with other science teams within Perso Engine to holistically solve a buyer problem.

• Coach and develop career opportunities for team members.

• 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.

• M.S. or PhD in Machine Learning or related Engineering field.

• 1+ years of People  Management experience

• Previous Hands-on ML experience in ranking problems. A prior experience as a Staff Level Machine Learning Scientist is a must.

• You are an excellent coach, mentor, and developer of engineers. 

• Ideally, you are familiar with modern machine learning frameworks such as TensorFlow or PyTorch. 

• Excellent written and oral communication skills, comfortable working with groups outside engineering, and able to convey technical information to non-engineers when needed.