Senior ML Scientist, Advertising Optimization

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 Advertising business is rapidly expanding, adding hundreds of millions of dollars in profits to Wayfair. We are building Sponsored Products, Display & Video Ad offerings that cater to a variety of Advertiser goals while showing highly relevant and engaging Ads to millions of customers. We are evolving our Ads Platform to empower advertisers across all sophistication levels to grow their business on Wayfair at a strong, positive ROI and are leveraging state of the art Machine Learning techniques.

The Advertising Optimization & Automation Science team is central to this effort. We leverage machine learning and generative AI to streamline campaign workflows, delivering impactful recommendations on budget allocation, target Return on Ad Spend (tROAS), and SKU selection. Additionally, we are developing intelligent systems for creative optimization and exploring agentic frameworks to further simplify and enhance advertiser interactions.

We are looking for an experienced Senior Machine Learning Scientist to join the Advertising Optimization & Automation Science team. In this role, you will be responsible for building intelligent, ML-powered systems that drive personalized recommendations and campaign automation within Wayfair's advertising platform. You will work closely with other scientists, as well as members of our internal Product and Engineering teams, to apply your ML expertise to define and deliver 0-to-1 capabilities that unlock substantial commercial value and directly enhance advertiser outcomes.

What You'll do

• Design and build intelligent budget, tROAS, and SKU recommendations, and simulation-driven decisioning that extends beyond the current advertising platform capabilities.
• Lead the next phase of GenAI-powered creative optimization and automation to drive significant incremental ad revenue and improve supplier outcomes.
• Raise technical standards across the team by promoting best practices in ML system design and development.
• Partner cross-functionally with Product, Engineering, and Sales to deliver scalable ML solutions that improve supplier campaign performance. Ensure systems are designed for reuse, extensibility, and long-term impact across multiple advertising workflows.
• Research and apply best practices in advertising science, GenAI applications in creative personalization, and auction modeling. Keep Wayfair at the forefront of innovation in supplier marketing optimization.
• Collaborate with Engineering teams (AdTech, ML Platform, Campaign Management) to build and scale the infrastructure needed for automated, intelligent advertising decisioning.

We Are a Match Because You Have:

• Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related field.
• 9 years of experience in building large scale machine learning algorithms.
• 4 years of experience working in an architect or technical leadership position.
• Strong theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, transformers and NLP techniques.
• Proficiency in programming languages such as Python and relevant ML libraries (e.g., TensorFlow, PyTorch) to develop production-grade products.
• Strategic thinker with a customer-centric mindset and a desire for creative problem solving, looking to make a big impact in a growing organization.
• Demonstrated success influencing senior level stakeholders on strategic direction based on recommendations backed by in-depth analysis; Excellent written and verbal communication.
• Ability to partner cross-functionally to own and shape technical roadmaps

Intellectual curiosity and a desire to always be learning

Nice to have

• Experience with GCP, Airflow, and containerization (Docker).
• Experience building scalable data processing pipelines with big data tools such as Hadoop, Hive, SQL, Spark, etc.
• Familiarity with Generative AI and agentic workflows.
• Experience in Bayesian Learning, Multi-armed Bandits, or Reinforcement Learning.