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Senior Machine Learning Engineer (m/f/x)
  • Python
  • Spark
  • SQL
  • Java
  • Machine Learning
  • Big Data
  • Excel
  • Scala
  • Kafka
131 days ago

About The Team

Wayfair’s EU Data Science team builds the algorithmic systems that drive our business. The team has a wide range of scope: fraud detection, supply chain operations, customer feedback and translations. As a result, we work with several different engineering teams in different departments for our model productization.

As Senior Machine Learning Engineer, you will partner with our Fraud Prevention engineering team to productionize cutting-edge fraud detection models. This is the newest global domain run from our Berlin office. Its mandate is to make sure that fraudsters stay out, while legitimate customers aren’t blocked from shopping for their home.

Handling fraud attempts at our scale is a huge, but exciting challenge. In 2019, Wayfair served >20M customers and generated revenue of >$9B growing >20%.

The projects that our teams work on are built from the ground up – we look for entrepreneurial individuals who want to take ownership over their own agenda and thrive in a collaborative team environment.

What You'll Do:

  • Deploy and maintain production models using both internal and external solutions
  • Collaborate closely with the Fraud Engineering team to ensure integration of real time data pipeline and machine learning model into overall fraud prevention system
  • Improve the pace of innovation and experimentation by introducing best practices and tools for Data Science workflow and DevOps
  • Develop GCP based solutions within EU Data Science team and help establish our team as the center of excellence for GCP
  • As a senior engineer, you will help grow other engineers by mentoring and developing learning opportunities

What You'll Need:

  • Bachelor’s Degree in Computer Science or related field
  • 5+ years of previous experience in software engineering with industry experience in Machine Learning
  • Ability to architect scalable distributed computing systems for machine learning
  • Familiarity with machine learning and parallel processing pipelines, experience with implementation in low-latency real-time platforms and/or scalable offline batch processes
  • Solid experience with Python (production level code), SQL and cloud-based solutions (preferably GCP)
  • Job scheduling technologies (Airflow, etc.) and containerization for isolated development (Docker, Kubernetes) shouldn’t be foreign concepts to you
  • Ability to communicate technical subject matter to non-experts
  • Desire to always be learning, and a collaborative team-player attitude!

Nice to have would be some experience with:

  • Java or Scala
  • Proficiency in Big Data and Streaming tech (Spark, Kafka, etc)
  • Previous exposure to Fraud/Payments projects

About Us:

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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