Senior ML/Data Engineer

San Francisco, CA

Full Time Senior-level / Expert
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Wayfair Inc.
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Posted 1 month ago

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 unified Data and Machine Learning platform and services. We are looking for a highly technical, hands-on, and mission-driven Engineer to be part of an amazing team.

Responsibilities

  • Deliver Data Engineering capabilities for streaming and batch based data ingestion, enrichment and aggregation.
  • Enable Data Quality for complex DAGs.
  • Build and operate tools, services and infrastructure we use to enrich and label the data, create features, train, evaluate and serve both online and offline models.
  • Partner closely with the Data Scientists and Product Managers for multiple initiatives.
  • Work in a fast paced environment to deliver results.
  • Provide engineering expertise to the quarterly and annual planning exercises.
  • Work closely with central platform teams to build the data and ML solutions.

Requirements

  • You have 5+ years of experience as a Software or Data Engineer.
  • You have experience as a Data or Machine Learning Engineer and successfully delivered business critical predictive capabilities.
  • You are a mentor to the junior engineers, 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 Data Engineering and ML systems deployed at scale.
  • You keep up with the industry trends and continuously identify new tools to use to solve technical problems.

Technical skills

  • 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.

Job region(s): North America
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