Machine Learning, Content and Navigation

Machine Learning, Content and Navigation 🚀 JOIN THE FUTURE OF COMMERCE WITH WHATNOT! Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. We’re re-defining e-commerce by blending community, shopping, and entertainment into a community just for you. As a remote co-located team, we’re inspired by innovation and anchored in our values https://www.whatnot.com/careers. With hubs in the US, UK, Germany, Ireland, Poland, and Australia, we’re building the future of online marketplaces –together. From fashion, beauty, and electronics to collectibles like trading cards, comic books, and even live plants, our live auctions have something for everyone. And we’re just getting started! As one of the fastest growing marketplaces https://a16z.com/marketplace-100/, we’re looking for bold, forward-thinking problem solvers across all functional areas. Check out the latest Whatnot updates on our news https://blog.teamwhatnot.com/ and engineering https://medium.com/whatnot-engineering blogs and join us as we enable anyone to turn their passion into a business, and bring people together through commerce. 💻 ROLE The Discovery Content and Navigation (CAN) team’s mission is to capture intent and content signals to build a seamless, engaging, and personalized navigation experience for Whatnot buyers. We’re passionate about enabling and maintaining a healthy discovery ecosystem—one where buyers can easily find fun shows and connect with sellers. Our work spans a wide range of problems, including search, taxonomy, events, and intent and content understanding. We leverage AI technology, make data-informed decisions, and ship quickly to deliver value to our users. What you'll do: - Lead the design, development, and productionization of ML models to capture intent and content signals that powers personalized navigational experience, search, and recommendations - Lead ML-based projects from end-to-end: scoping and planning, data collection and feature engineering, model training and deployment, backend implementation, and online experimentation - Support product initiatives like category and brand recommendations, promote high quality and relevant livestreams and products in feed and search. - Work closely with teammates and cross-functional partners to implement ML-based solutions into production at scale - Drive technical excellence and establish ML best practices across the team and org. US Based: We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our New York, San Francisco, Los Angeles, and Seattle hubs. 👋 YOU Curious about who thrives at Whatnot? We’ve found that embodying a low ego, growth mindset, and high-impact drive goes a long way here. As our next Machine Learning Engineer you should have 4+ years of generalist software development experience in high growth startups, plus: - 4+ years of industry experience building and deploying ML models to solve user problems at scale. - Industry experience with a track record of applying practical methods to solve real-world problems on consumer scale data. - Experience in applied statistical and machine learning fields e.g. search, recommendations, content understanding, natural language processing, and large language models. - Proficiency in Python, SQL, and common ML frameworks. - Strong communication and leadership skills; ability to influence roadmap and align cross-functional teams in a remote environment. - Excellent product instincts. You first think about users rather than the best technical solution. - You are known for shipping products and features lightning-fast. 💰COMPENSATION For Full-Time (Salary) US-based applicants: $245,000/year to $345,000/year + benefits + equity. The salary range may be inclusive of several levels that would b ... (truncated, view full listing at source)