Machine Learning Manager, Wayfair

• 7+ years of experience in applied Machine Learning with 2+ years in a people leadership or technical lead role
• Proven experience building and deploying ML systems across a range of domains (especially in tabular data, computer vision, or NLP) in production environments
• Proficiency in Python, SQL, and industry-standard ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow), MLOps platform
• Strong track record of developing ML solutions from ideation through delivery
• Strong communication and stakeholder management skills; able to translate technical work into strategic decisions

Desirable

• The Machine Learning Science team within Wayfair’s Supply Chain & Retail Tech organization is focused on building intelligent, scalable systems that optimize the customer journey, uplevel customer experience, and streamline operational efficiency across our service and logistics ecosystem
• Our work touches millions of customers and thousands of support and fulfillment associates every day
• We develop models that personalize customer service, detect and prevent fraud, and apply computer vision to automate everything from customer issue resolution to warehouse quality control
• These systems are deeply embedded in real-time business processes and drive measurable value for both our customers and Wayfair’s bottom line
• We are seeking a Machine Learning Science Manager to lead a high-performing team of ML scientists
• In this role, you’ll drive the scientific strategy, coach and develop your team, and play a key role in shaping the multi-year ML roadmap—working cross-functionally to define priorities, align on vision, and turn complex problems into production-ready solutions
• To get a better sense of the type of projects we actually work on, check out our Data Science & Machine Learning blog posts here!
• Lead and mentor a team of Machine Learning Scientists working across a portfolio of projects, including:
• Service Personalization: Build real-time models that enable tailored customer service experiences via dynamic routing, predictive eligibility, and refund abuse prevention
• Computer Vision: Use CV techniques to interpret customer-uploaded images, automate damage detection, and improve fulfillment operations
• Define and drive the team’s scientific and strategic direction, contributing to the multi-year roadmap in partnership with cross-functional stakeholders
• Translate ambiguous, high-impact business challenges into clearly scoped ML initiatives with measurable goals and aligned timelines
• Balance near-term delivery with long-term innovation, ensuring the team is focused, resourced, and aligned with evolving business needs
• Collaborate cross-functionally to integrate ML systems into core business operations, ensuring scalability and business impact
• Foster a collaborative, growth-oriented team culture, supporting professional development and technical mentorship