Machine Learning Engineer, Personalization

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. With hubs in the US, UK, Germany, Ireland, and Poland, 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, 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.

• Lead the design, development, and productionization of ML models that power feed recommendations and buyer personalization

• 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 exploration and international, new buyer, new seller, and small category growth.

• Work closely with Backend Software Engineers to implement ML-based solutions into production

• Drive technical excellence and establish ML best practices across the Buyer and Discovery teams, working closely with our Machine Learning Platform team. Grow ML knowledge across the team and support the scalability of our production models

US Based:

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

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 Scientist you should have:

• 4+ years of industry experience building and deploying ML models to solve user problems at scale

• Industry experience with a track record of applying scientific methods to solve real-world problems on consumer scale data.

• Advanced proficiency in Python, SQL, and common ML frameworks like PyTorch, XGBoost, etc

• Strong communication and leadership skills; ability to influence roadmap and align cross-functional teams in a remote environment.

• Proficiency and experience in applied statistics. Firm grasp of visualization tools, interactive and self-serving, such as dashboards and notebooks.

• Preferred Qualifications:

  • Experience building ML applications for Discovery and Personalization domains

  • Experience with backend development

For Full-Time (Salary) US-based applicants: $175,000/year to $195,000/year + benefits + equity.

The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.

• Flexible Time off Policy and Company-wide Holidays (including a spring and winter break)

• Health Insurance options including Medical, Dental, Vision

• Work From Home Support

  • Home office setup allowance

  • Monthly allowance for cell phone and internet

• Care benefits

  • Monthly allowance for wellness

  • Annual allowance towards Childcare

  • Lifetime benefit for family planning, such as adoption or fertility expenses

• Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally

• Monthly allowance to dogfood the app

• Parental Leave

  • 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.

Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.