Location
San Francisco, CA, Seattle, WA, Los Angeles, CA, New York, NY
Employment Type
Full time
Location Type
Remote
Department
Engineering
Buyer Engineering
Compensation
$235K – $270K • Offers Equity
The salary or hourly rate range may be inclusive of several levels that would be applicable to the position. Final salary or hourly rate will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary or hourly rate, not benefits or equity.

JOIN THE FUTURE OF COMMERCE WITH WHATNOT!

Whatnot is the largest livestream 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. With hubs in the US, UK, Ireland, Poland, and Germany, we’re building the future of online marketplaces—together.
From fashion, beauty, and electronics to rare 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, we’re looking for bold, forward-thinking problem solvers across all functional areas. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business, and bring people together through commerce.
Role

The Buyer Growth team is responsible for driving Whatnot’s top-of-funnel growth and first-time buyer success. We’re looking for a Machine Learning Engineer to accelerate buyer growth at Whatnot through intelligent, data-driven experiences. As the first ML engineer, you’ll build and own ML models personalization in onboarding and user targeting in our acquisition and engagement channels. This is a high-impact role on a team directly responsible for growing Whatnot’s buyer base and improving first-time user conversion. In this role, you will

• Lead the design, development, and productionization of ML models that power user acquisition, activation, and retention (e.g., ranking models, targeting systems, uplift modeling).
• Own the full model lifecycle: from data collection and feature engineering to model training, evaluation, deployment, and online experimentation.
• Identify and prioritize high-impact opportunities where machine learning can unlock growth, collaborating with product, engineering, data, and marketing stakeholders.
• Drive technical excellence and establish ML best practices across the Buyer Growth team.

Team members in this role are required to be within commuting distance of our Los Angeles, San Francisco, Seattle, or New York hubs.
You

Curious about who thrives at Whatnot? We’ve found that low ego, a growth mindset, and leaning into action and high impact goes a long way here.

• 8+ years of industry experience building and deploying ML systems at scale.
• Demonstrated success in leading end-to-end ML projects that drove measurable business outcomes.
• Deep expertise in personalization, ranking, or user modeling; strong intuition around user behavior in consumer products.
• Advanced proficiency in Python, SQL, and common ML frameworks (e.g., PyTorch, TensorFlow, XGBoost).
• Strong communication and leadership skills; ability to influence roadmap and align cross-functional teams.
• Preferred Qualifications:
• Experience building ML applications in E-commerce or Social products
• Prior experience in growth domains: user segmentation, retention modeling, large scale recommendation systems, notification ranking, etc.

• Lead the design, development, and productionization of ML models that power user acquisition, activation, and retention (e.g., ranking models, targeting systems, uplift modeling).
• Own the full model lifecycle: from data collection and feature engineering to model training, evaluation, deployment, and online experimentation.
• Identify and prioritize high-impact opportunities where machine learning can unlock growth, collaborating with product, engineering, data, and marketing stakeholders.
• Drive technical excellence and establish ML best practices across the Buyer Growth team