Machine Learning Engineering Manager
Wayfair believes everyone should live in a home they love. Through technology and innovation, we make it possible for customers to quickly and easily find exactly what they want from a selection of millions of items across home furnishings, décor, home improvement, housewares and more. The Catalog Data Science team at Wayfair uses Data Science and ML capabilities for building predictive models to launch products that offer best value for its customers with a wide variety of personalized selection. The most complex and business critical Data Science models deliver fast, scalable, easily accessible, and reliable comparisons between large numbers of products in the catalogs. These comparisons enable Wayfair to make better decisions across many teams including Merchandising, Pricing, Marketing, Search & Recommendations, and Category Management.
To enable these predictive analytics capabilities we need a robust, scalable and easy to use Machine Learning platform and services. We are looking for a highly technical, hands-on, and mission-driven Engineering Manager to lead our Machine Learning team to help us scale to the next level. As a Sr Manager reporting to the Head of ML Engineering, you will have engineering leadership and influence on the evolution of the machine learning systems and applications.
- Build and operate the tools, services and infrastructure we use to enrich and label the data, create features, train, evaluate and serve both online and offline models.
- Build and lead a team of highly-engaged engineers by hiring, coaching, and instilling a sense of ownership and impact.
- Build the vision and roadmap for the Machine Learning team by working with Product and Data science teams.
- Manage processes and use technical expertise to continually ensure that your team delivers business impact.
- Define OKRs for your team and achieve positive measurable results.
- Work with other Engineering Managers to improve the ML Engineering organization.
- You have 5+ years of experience as a Software or Data Engineer.
- You have experience as an Engineering Manager and successfully managed a team of 5+ Software or Data Engineers and Technical Leads.
- You are a mentor, and you're great at coordinating with a variety of teams throughout the company.
- You excel in undefined environments and get excited about finding solutions to complex technical challenges, and then building them.
- You enjoy coming up with pragmatic solutions to concrete problems using strategic thinking.
- You've worked with complex distributed machine learning systems deployed at scale.
- You keep up with the industry trends and continuously identify new tools to use to solve technical problems.
- Proficiency in programing languages including Java, Python, Scala
- Experience in containerization and orchestration including Docker, Kubernetes, and Airflow
- Data ingestion and processing frameworks including Kafka and Spark.
- Cloud Infrastructure- GCP or AWS or Azure
About Wayfair Inc.
Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston or Berlin, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you’re looking for rapid growth, constant learning, and dynamic challenges, then you’ll find that amazing career opportunities are knocking.
No matter who you are, Wayfair is a place you can call home. We’re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why we’re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.
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