By applying to this position, your application is automatically considered for the range of Data Science Tech Lead roles we have at Wayfair. If we think you might be a fit, a recruiter will reach out to learn more about your background and discuss relevant positions in more detail.
Who we are
The ML Engineering - Marketing team at Wayfair develops scalable data-processing platforms and deploys hundreds of machine learning models that power algorithmic decision-making across many marketing channels and customer touchpoints. While data science is at the heart of everything we do, it is our ML engineering team that enables us to scale our impact and quickly turn our ideas into models, models into decisions, and into new customer experiences. Our team aims to redefine how we think about label and feature generation, model development, deployment, and monitoring.
The Associate Director, ML Engineering will be responsible for growing and leading a lean and mean high-performance engineering team that deploys and maintains 500+ ML models scoring 100M+ customers/devices on a daily basis. The portfolio of ML model and analytical services our team develops powers the way millions of customers interact with us. This role represents significant technical, analytical, and leadership opportunities with enormous potential for business impact. You will also have the opportunity to dive deep into the technical details, future-proof our ML tech stack, and pioneer novel platforms while simultaneously defining and communicating out your technical vision to the broader organization.
What youll do
- Hire, coach, and mentor a high-performing team of ML engineers and data engineers
- Develop and deliver on technical roadmaps and architectures for your portfolio products designed to accelerate development of highly scalable machine learning systems
- Future-proof our ML tech stack, and pioneer novel platforms while simultaneously defining and communicating out your technical vision to the broader organization.
- Partner closely with partner engineering, science, and infrastructure teams to ensure our org has the data, computing resources, and tooling needed to do our best work.
- Advise engineering and product management on technical roadmap, ensuring that the vision aligns with broader company objectives
- Promote a culture of engineering excellence and provide sound technical leadership
- Define and advance MLOps best practices within ML & data science 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.
What youll need
- 8+ years experience as a ML Engineer/Data Engineer/Data Scientist with a strong software engineering background.
- 5+ years of experience managing Software Engineers, ML Engineers, data scientists and interfacing with cross-functional stakeholders
- Experience building and deploying ML Pipeline at scale and leading Operational excellence for the team.
- Hands-on manager with ability to get into the weeds and provide deep technical coaching and mentorship to direct reports.
- 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.
- Great problem solving capabilities, troubleshooting data issues and experience in stabilizing big data systems.
- Ability to work on cross-functional projects and manage multiple stakeholders with competing priorities.
- 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.
Its 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 worlds 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, were 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 youre looking for rapid growth, constant learning, and dynamic challenges, then youll find that amazing career opportunities are knocking.
No matter who you are, Wayfair is a place you can call home. Were 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. Thats why were 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.