Manager, Machine Learning Engineering
Remote, US
At GOAT Group, the Engineering team is an integral part of our dynamic company. By joining the team, your skills will be front and center, working alongside other passionate individuals to solve problems and build software. From launching compelling new consumer experiences, tackling global logistics challenges to scaling infrastructure to facilitate our rapid growth – technology is essential to driving our vision forward. The work you do will change the way the world shops, while also empowering entrepreneurs, including individual sellers, brands and boutiques.
The Machine Learning Engineering team supports almost every part of the business, including operations, fulfillment, recommendations, search, fraud detection, marketing, business development, and many more. The team uses ML together with GOAT's massive scale and data to maximize impact across the company. At GOAT, Machine Learning Engineers are expected to work full-stack and end-to-end, from communicating with stakeholders and coming up with project ideas all the way to deploying models to production. We work closely with the Machine Learning Platform team to develop the tools and systems necessary to enable this. This is an opportunity to lead the team and help set its direction.
The company is backed by strategic investor Foot Locker, Inc. as well as some of the leading names in venture capital including D1 Capital Partners, Accel, Andreessen Horowitz, Index Ventures, Matrix Partners, Upfront Ventures, Webb Investment Network and Y Combinator.
We encourage you to apply even if you feel unsure about whether you meet every single requirement. We look for people who are passionate about what we do, not just those who check off all the boxes.
The Machine Learning Engineering team supports almost every part of the business, including operations, fulfillment, recommendations, search, fraud detection, marketing, business development, and many more. The team uses ML together with GOAT's massive scale and data to maximize impact across the company. At GOAT, Machine Learning Engineers are expected to work full-stack and end-to-end, from communicating with stakeholders and coming up with project ideas all the way to deploying models to production. We work closely with the Machine Learning Platform team to develop the tools and systems necessary to enable this. This is an opportunity to lead the team and help set its direction.
In this role you will:
- Manage and grow a team of Machine Learning Engineers
- Mentor the team of MLEs and grow them to become experts in their domain
- Set the technical vision and drive the long-term ML strategy for the organization
- Build the brand and market the team externally through blogs, talks and podcasts
- Evangelize ML throughout the organization, communicating results and methodology effectively within the team and to external stakeholders
- Work closely with the Machine Learning Platform team to help shape their overall roadmap and accelerate the impact of ML throughout the organization
We are looking for:
- 6+ years of industry experience in machine learning (bonus points for e-commerce and/or marketplace experience)
- 2+ years of experience leading machine learning projects/teams
- Experience recruiting and growing teams a plus
- A track record of shipping large-scale, high-impact machine learning solutions to production
The company is backed by strategic investor Foot Locker, Inc. as well as some of the leading names in venture capital including D1 Capital Partners, Accel, Andreessen Horowitz, Index Ventures, Matrix Partners, Upfront Ventures, Webb Investment Network and Y Combinator.
We encourage you to apply even if you feel unsure about whether you meet every single requirement. We look for people who are passionate about what we do, not just those who check off all the boxes.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: E-commerce Engineering Machine Learning
Perks/benefits: Career development Startup environment
Regions:
Remote/Anywhere
North America
Country:
United States
Job stats:
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Categories:
Engineering Jobs
Leadership Jobs
Machine Learning Jobs
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