Job description

🚀 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. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops. As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact. We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. 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 • 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. Contribute to backend development to support recommendations and feed work. • Drive technical excellence and establish ML best practices across the Buyer and Discovery teams, working closely with our Machine Learning Platform and Research teams. 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 one of our hubs: NYC, SF, LA, SEA. 👋 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 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 💰Compensation 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 in the form of stock options. 🎁 Benefits • 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 • All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!). • 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. Please note: Whatnot will only contact you through official @whatnot.com email addresses. If you see an email impersonating a Whatnot recruiter, please disregard and report it as spam. 💛 EOE 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.

Requirements

Must-haves

Join the Future of Commerce with Whatnot!
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. Contribute to backend development to support recommendations and feed work.
Team members in this role are required to be within commuting distance of one of our hubs: NYC, SF, LA, SEA.
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.

Nice-to-haves

Experience building ML applications for Discovery and Personalization domains
Experience with backend development

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlmachine learningpythonsql

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401k

Parental Leave

Wellness