What you'll do
- Lead and grow a high-performing machine learning and personalization team focused on product recommendations, search, and site monetization.
- Drive the technical direction for ML systems including homepage feed and 'add next' experience to maximize revenue and user value.
- Manage a multidisciplinary pod including ML Engineers, Software Engineers, Product Manager, and Designers with a hands-on leadership style.
- Own the full ML lifecycle from data pipelines, modeling, deployment, to monitoring and iteration in production environments.
- Collaborate cross-functionally with Product, Design, Analytics, and Data teams to translate business problems into technical solutions.
What you should know
- This role offers career growth with opportunities to build and lead a specialized ML function within a high-impact consumer product.
- Candidates should be prepared for a hands-on leadership role requiring both technical fluency and people management skills.
- Working here means engaging with large-scale, real-time data systems and complex user journeys in an e-commerce context.
- Applicants must be comfortable working in an AI-integrated environment where AI tools support daily workflows and innovation.
- The company values product-minded leaders who focus on solving real user problems and driving measurable business outcomes.
About the company
- Babylist is a leading registry and e-commerce platform serving over 9 million users annually in the baby product industry.
- The company has a strong mission to support growing families with trusted guidance and expert product recommendations.
- Babylist operates as a remote-first company with HQ team members across the U.S. and Canada and biannual in-person meetings.
- They emphasize a culture of focus, intention, and recharging, with strong investment in exceptional management and employee connection.
- Babylist is an AI-forward organization embedding AI tools in daily operations to drive innovation and impact.
Key required skills
Pythonpandasscikit-learnxgboostPyTorchAirflowMachine LearningData ScienceML lifecyclePersonalization