Staff Machine Learning Engineer

This is a fully remote position, open to applicants in Canada, +1 more country.

📋 Description

• Take charge of recommendations and personalization within Babylist's consumer experience, encompassing the homepage feed, product suggestions, search functionalities, and machine learning-driven systems.

• Establish the technical roadmap for personalization initiatives over the next one to two years.

• Direct product recommendations across product detail pages, registry add-next suggestions, and visual representations of products.

• Tailor the Feed's selection and ordering of product, editorial, and social content.

• Customize search results utilizing family signals and synchronize search retrieval and ranking with recommendations.

• Enhance product suggestions for Addie, Babylist's AI registry assistant.

• Navigate ambiguous business challenges from initial concept to production models while owning their business impact.

• Make modeling and architectural choices that affect multiple product surfaces.

• Design evaluations for offline and online models before and after product launch.

• Decide when simple rules or baseline models are more effective than advanced modeling techniques.

• Collaborate with product, design, and data teams on project priorities.

• Mentor team engineers and act as a machine learning expert throughout the engineering organization.

⛳️ Requirements

• Experience in launching recommendation and/or personalization systems for real users at scale within a consumer product setting.

• Proven business impact resulting from recommendation or personalization projects.

• Proficient in recommender system fundamentals, including candidate generation vs. ranking, offline vs. online evaluation, cold start strategies, and managing position and popularity bias.

• Proficient in the Python machine learning stack.

• Comfortable overseeing models from deployment through monitoring stages.

• Experience contributing to an application backend.

• Ability to independently navigate through ambiguous problems.

• Knowledge of effort versus effectiveness tradeoffs in early-stage machine learning projects.

• Outcome- and user-focused approach linking model adjustments to user experience, registry additions, conversion rates, or revenue generation.

• Regular use of AI tools and an inquisitive mindset towards emerging AI capabilities.

🏝️ Benefits

• Target annual bonus of 20 percent of base salary.

• Significant equity offerings.

• 401(k) matching program.

• Company-paid health insurance.

• Comprehensive dental and vision coverage.

• Generous paid parental leave for both birthing and non-birthing parents.

• Gradual return-to-work program.

• Winter Wonder Week, a paid week off for the entire company at the year's end.

• Stipend for remote work expenses.

• Support for mental health and wellness.

• Remote-first work environment across the US and Canada.

• Biannual company-wide in-person gatherings.