About the position
Etsy is seeking an Engineering Manager to lead the machine learning team that is improving the fulfillment experience for both buyers and sellers. You'll help deliver robust, scalable production models that will be A/B tested live on Etsy.com. Staying at the forefront of the ML field, you'll bring its best ideas to life for millions of Etsy shoppers. Your team will test new ideas, and pioneer solutions from the ground up, being responsible for the end-to-end ML lifecycle. This is a full-time position reporting to the Director of Engineering within the Inventory & Fulfillment Systems team, which focuses on high impact improvements for connecting buyers to items that meet their shopping mission and supports sellers in meeting buyer expectations. 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.
Responsibilities
- Lead the ML team within the context of product engineering, establishing effective processes that increase collaboration across disciplines.
- Lead a fast paced, data-driven, and agile team of 5-9 machine learning scientists and engineers to build systems that measurably improve the buying experience in close partnership with product teams.
- Take part in the end-to-end recruiting process, hiring and on-boarding exceptional engineering talent.
- Serve as a coach, mentor, and advocate for the engineers on your team.
- Work with other leaders within engineering to develop and evolve engineering processes and standard methodologies.
- Establish strong cross-functional relationships with product engineers, product managers, user researchers, designers, analysts as well as platform, data, and infrastructure teams.
- Leverage established tools built by our ML platform teams and help create new paved paths within product engineering context.
Requirements
- Strong hands-on end-to-end Machine Learning experience (experimentation, high volume data & data processing, model deployment, best practices)
- Experience managing & mentoring Applied Scientists, ML Engineers & SWEs, and collaborating with non-ML teams.
- Excellent communication skills for both technical and non-technical collaborators, both written & verbal.
- Experience shaping team processes and technical strategy for effective delivery.
- Empower & unblock your team in pursuit of high-quality technical decisions.
- Proficiency in applying team processes for efficient product delivery and thriving in metric-driven environments along with a focus on quality documentation.
Benefits
- Equity package
- Annual performance bonus
- Competitive benefits that support you and your family
