Senior Machine Learning Engineer, Marketing Data Science
Wayfair Inc.Shop Wayfair for A Zillion Things Home across all styles and budgets. 5,000 brands of furniture, lighting, cookware, and more. Free Shipping on most items.
Who we are
Wayfair is moving the world so that anyone can live in a home they love – a journey enabled by more than 3,000 Wayfair engineers and a data-centric culture. Wayfair’s Data Science Marketing team builds algorithmic systems that drive our business, enhance customer experience, and improve customer loyalty. You will be part of a cross-functional, collaborative team driving development of world-class ML systems that improve our customer understanding and marketing decisions.
What you’ll do
- Own and contribute to the ML Pipeline development lifecycle from Data wrangling, Feature development, Training and tuning ML model with Data Scientist, Deploy and manage the Inference Pipeline.
- Develop a reusable code and pattern to scale the ML Pipeline to new business use cases and create a self service platform.
- Partner closely with the ML Platform team, Infrastructure team, and similar teams to ensure the Data science org has the data, computing resources, and workflows/abstractions needed to do our best work.
- Contribute to the roadmap, and project execution with cross-functional stakeholders and Eng partner teams.
- Define and advance MLOps best practices within data science and product teams
- Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on.
- Contribute to SME initiative and code review in support of spreading best practices
What you’ll need
- 4+ years experience as a ML Engineer, Data Engineer, Data Scientist with strong engineering skills and a passion for working on turning reference implementations into production-ready software.
- Proficiency in at least one high-level programming language (Python, Java, Scala or equivalent) used both for ML and automation tasks.
- Experience with Python ML ecosystem (numpy, pandas, sklearn, XGBoost, etc.) and Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML)
- Hands-on experience building scalable ML & big data processing pipelines with big data tools such as Hadoop, Hive, SQL, Spark and GCP cloud services such as DataProc, BigQuery, GCS etc.
- Experience with automated data pipeline and workflow management tools, i.e. Airflow.
- Strong sense of ownership and growth mindset.
- Experience with basic software engineering tools, e.g., git, CI/CD environment (such as Jenkins or Buildkite), PyPi, Docker, Kubernetes, unit testing, and general object-oriented design.
It’s Great if You Have
- PhD or MSc or Bsc in Computer Science / Operations Research / Statistics or other quantitative fields
- Experience with common ML frameworks/libraries such as Vowel wabbit, Tensorflow, PyTorch is preferred.
- Experience with Cloud Services such as AWS SageMaker/GCP AI Platform.
- Deploying and scaling ML solutions using open-source frameworks (MLFlow, TFX, H2O, etc.)
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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