Machine Learning Tech Lead -Marketing

Boston, MA

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Wayfair Inc.
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Posted 1 week ago

The ML Engineering team within the Marketing Data Science team at Wayfair develops scalable data processing platforms and deploys hundreds of machine learning models that power algorithmic decision-making across dozens of marketing channels and customer touchpoints. 

 

Data is at the heart of everything we do and ML data engineering is crucial to our ability to scale as we train and deploy the next generation of ML products at Wayfair that power the way millions of customers interact with us. You will be processing petabytes of un/structured first party and third party and building signal processing capabilities that can transform billions of data points into meaningful feature representations suitable for accelerated model development. The tools we’ve built thus far and the new capabilities we have on our roadmap aim to redefine how we think about label and feature generation, model training, deployment, and monitoring. 

 

Above all, you’ll get to work on problems that are both intellectually-challenging and drive real, measurable impact, first and foremost, for our customers - and as a result for Wayfair at large. To get a better sense of the type of projects we actually work on, check out our Data Science & Machine Learning blog posts here!

 

What You'll Do

  • Build highly scalable distributed data processing platforms that power hundreds of production ML models and analytical services that impact our business
  • Collaborate with other data scientists to build high quality ML models that can robustly scale up to large volumes in production
  • Research, procure, select, and ingest appropriate datasets and data representation methods for various problem domains (paid media, sales, service, marketing)
  • Partner closely with various business & engineering teams to drive the integration of our model outputs & algorithmic decision-making systems into existing production systems
  • You’ll be a builder of tools, software, and microservices that enhance or streamline various steps or challenges within the data science workflow & our tech stack
  • Extend existing ML libraries and frameworks for scalable model training & deployment
  • Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on

 

What You'll Need

  • 4+ years of experience working as a professional software developer, ML Engineer, or Data Scientist (with a strong engineering skills & interest in software development)
  • BSc, MS, or PhD in a quantitative field (e.g. mathematics, computer science, engineering, operations research, physics, economics, neuroscience, etc.)
  • Strong programming skills in Python or Java and some exposure to the Python ML ecosystem (numpy, panda, sklearn, tensorflow, etc.)
  • Familiarity with large-scale data processing and distributed systems (Hadoop, Spark, etc.)
  • Experience with CI/CD environment (such as Jenkins or Buildkite), version control (Git), job orchestration (e.g. Airflow), and artifact management such as PyPi (nice to have)
  • Exposure to machine-learning model lifecycle; training, evaluation, serving
  • Interest in deploying machine-learning models as scalable services
  • Interest in ML tool-making; building capabilities for other developers/scientists and empowering them to be more efficiently build better ML software
  • Desire to work in a collaborative environment focusing on continuous learning; writing blog posts, participating in tech talks, conducting code reviews, etc.
  • You don’t have to be an expert in all or any of the above areas but we need someone with a passion for learning and growing as a software developer and ML engineer

It's a bonus to have:

  • Experience with any of: Airflow, Docker, Spark, GCP, Kubernetes, Snowflake.
  • Experience writing, testing, and interpreting numerical, scientific code.
  • Expertise in object-oriented programming and software design

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 tags: Airflow Distributed Systems Economics Engineering Hadoop Java Kubernetes Machine Learning Marketing ML NumPy Python Research Spark TensorFlow
Job region(s): North America
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