Engineering Manager, ML Training Data Team

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 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:

What’s the role?

As the Engineering Manager you will be responsible for building and scaling our ML Training data team at Etsy. We are working on cutting-edge foundational tools at Etsy that accelerate model prototyping and development by generating datasets for model training with point-in-time accuracy, ensuring minimal training-serving skew. It's an integral part of our ML Enablement efforts, enhancing the efficiency and accuracy of our data-driven solutions, that will support various high visibility Machine Learning teams at Etsy including Search Ranking, Personalized Recommendations, etc.

Do you find joy in sophisticated architectures that involve leading highly performant teams specializing in distributed systems, machine learning and multiple collaborators? If so, this could be the perfect match.

This is a full-time position reporting to the Senior Engineering Manager, ML Enablement. 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 Training data team is part of the ML Enablement organization. Our mission is to enable efficient and impactful machine learning across Etsy as a platform. The broader ML Enablement team maintains systems that enable feature creation, storage, retrieval, as well as embeddings workflows that power personalized search, recommendations, and more. Our work drives innovation and enhances the experience for millions of Etsy buyers and sellers.

As a platform team with a customer focussed perspective, we tackle meaningful, complex challenges and build scalable solutions, enabling impactful contributions.

What does the day-to-day look like?

• Manage and grow a team of outstanding machine learning engineers, software engineers, and tech leaders to design, build, and support Etsy’s Training data systems.

• Collaborate with other leaders at Etsy to drive the technical and strategic vision for advancing ML technology with a focus on ML infrastructure tools for generating training datasets for model training with point-in-time accuracy.

• Define the roadmap and supervise its execution. You will connect and coordinate business initiatives and team priorities.

• Provide technical guidance to the team to build an infrastructure that helps scientists to build state of the art ML models.

• Cultivate a strong engineering culture, responsible for delivering business results with the right quality and in a timely fashion

• 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:

• Experience leading a team responsible for large-scale ML Infrastructure teams, with 7+ years of Software development experience including 2+ years of engineering management.

• A strong product sense: you take pride in building well designed products that ML practitioners love. Passion for translating the needs of ML practitioners into infrastructure offerings with an eye toward building large scale data systems to support ML training.

• Excellent at communicating context, giving and receiving feedback, fostering new ideas, and empowering others without micromanagement.

• ML practitioner leader or individual contributor experience owning end-to-end ML functions for a product domain.

• You have a background in Computer Science and related fields, equivalent to a B.S. degree or above in Computer Science, Electrical Engineering, Information Technology, or related engineering fields.

• You have practical experience in designing and architecting large-scale distributed systems and machine learning infrastructure.

• You possess strong proficiency in creating and optimizing large-scale Spark & Dataflow pipelines, as well as general data infrastructure technologies. This includes the ability to optimize storage formats and reduce job runtime & costs.

• You possess a strong understanding of ML foundations and extensive knowledge of the intricacies involved in ML development and training processes.