Babylist is looking to establish its first machine learning function to drive the next era of ML and personalization efforts, aiming to improve user experience and business outcomes by leveraging advanced recommendations and AI.
Requirements
- deep expertise in SQL and Python for machine learning applications
- proven track record of delivering production-grade ML solutions, ideally in recommender systems, personalization, or similar consumer-facing products
- understand the ML lifecycle end-to-end: experimentation, validation, rollout, and monitoring
- experience with distributed training frameworks, workflow orchestration (e.g., Airflow), and model monitoring tools
- relevant domain experience from consumer products such as e-commerce, dating apps, or platforms with complex user journeys
- highly autonomous, able to define problem spaces, architect solutions from zero to one, and operate with strong ownership
Responsibilities
- design, build, and optimize recommender systems that improve product and content discovery for millions of Babylist users
- taking machine learning models from prototype to scalable, production-ready deployments
- architecting the models behind our homepage feed, “add next” experience, and more
- framing problems with stakeholders to deployment, monitoring, and iteration
- advance Babylist’s personalization infrastructure
- delivering production-grade ML solutions, ideally in recommender systems, personalization, or similar consumer-facing products
- experimentation, validation, rollout, and monitoring
Other
- founding expert driving the next era of our machine learning and personalization efforts
- high-impact position designed for a hands-on engineer
- lead technical development within a focused product pod (Product Manager, Software Engineer, occasional Designer)
- help define how advanced recommendations and AI power our platform
- comfortable working in a small, agile pod while also helping shape the broader ML strategy across the organization
