Machine Learning Engineer, Discovery

📋 Job Overview

🚀 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.

🏢 About Whatnot

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.

🎯 The 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.

✅ Key Responsibilities

• 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
• Grow ML knowledge across the team and support the scalability of our production models

📌 Required Qualifications

• 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

⭐ Desirable Experience

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

🎁 Benefits

For US-based applicants: $180,000 - $245,000/year + benefits + stock options
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.

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.

🛂 Visa & Eligibility

US Based: Team members in this role are required to be within commuting distance of our New York City hub.