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 research projects across the marketplace dynamics problem area: simulation, auction and allocation mechanics, long-term objective modeling, exploration and information value, or marketplace experimentation methods • Take ideas from hypothesis to production: literature review, prototyping, offline validation, shadow testing, and online experiments shipped through partner teams in Discovery and the Seller org • Build models of how the marketplace behaves as a system: learned simulators that predict segment-level effects of ranking and policy changes, and surrogate models of long-term marketplace outcomes • Model Whatnot's actual market mechanics: auction and bidding dynamics, and discovery exposure allocation as a portfolio problem, including allocation to rising sellers • Advance how a multi-sided live marketplace evaluates changes: off-policy evaluation, switchback and interference-robust experiment designs, and variance reduction • Contribute to Whatnot's external technical presence through publications, open-source work, and public benchmarks NYC Based: Team members in this role are required to be within commuting distance (50 miles) of our New York City hub. 👋 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: • 5+ years of industry experience building and deploying ML models to solve user problems at scale • Depth in at least one of: recommendation systems, causal inference, off-policy evaluation, reinforcement learning and bandits, auction or mechanism design, or marketplace experimentation • 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 grounding in applied statistics, experiment design and theoretical machine learning • Strong communication and leadership skills; ability to influence roadmaps and align cross-functional teams in a remote environment • Preferred Qualifications: • Experience in two-sided marketplaces, ads and auction systems, or pricing • Experience building simulators or economic models of platform behavior 💰Compensation For Full-Time (Salary) US-based applicants: $210,000k/year to $300,000k/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. 🎁 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 • 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 research projects across the marketplace dynamics problem area: simulation, auction and allocation mechanics, long-term objective modeling, exploration and information value, or marketplace experimentation methods
Take ideas from hypothesis to production: literature review, prototyping, offline validation, shadow testing, and online experiments shipped through partner teams in Discovery and the Seller org
Build models of how the marketplace behaves as a system: learned simulators that predict segment-level effects of ranking and policy changes, and surrogate models of long-term marketplace outcomes
Model Whatnot's actual market mechanics: auction and bidding dynamics, and discovery exposure allocation as a portfolio problem, including allocation to rising sellers
Advance how a multi-sided live marketplace evaluates changes: off-policy evaluation, switchback and interference-robust experiment designs, and variance reduction
Contribute to Whatnot's external technical presence through publications, open-source work, and public benchmarks
Team members in this role are required to be within commuting distance (50 miles) of our New York City hub.
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:
5+ years of industry experience building and deploying ML models to solve user problems at scale
Depth in at least one of: recommendation systems, causal inference, off-policy evaluation, reinforcement learning and bandits, auction or mechanism design, or marketplace experimentation
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 grounding in applied statistics, experiment design and theoretical machine learning
Strong communication and leadership skills; ability to influence roadmaps and align cross-functional teams in a remote environment

Nice-to-haves

Experience in two-sided marketplaces, ads and auction systems, or pricing
Experience building simulators or economic models of platform behavior

Application prep

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Keywords to mirror

machine learningmlpythonsql

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401k

Parental Leave

Wellness