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 our New York City hub.
YouCurious 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
CompensationFor 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.
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.
