Whatnot
Machine Learning Engineer, Personalization
Whatnot, Los Angeles, California, United States, 90079
Overview
Join to apply for the
Machine Learning Engineer, Personalization
role at
Whatnot .
This range is provided by Whatnot. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Compensation Base pay range:
$175,000.00/yr - $195,000.00/yr
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 or equity.
Company overview Whatnot
is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. We’re redefining 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, Ireland, Poland, and Germany, we’re building the future of online marketplaces—together. From fashion, beauty, and electronics to rare collectibles like trading cards, comic books, and even live plants, our live auctions have something for everyone. 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 our 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.
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
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 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.
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
Preferred Qualifications:
Experience building ML applications for Discovery and Personalization domains
Experience with backend development
Compensation 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 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.
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.
Seniority level Mid-Senior level
Employment type Full-time
Job function Engineering and Information Technology
Industries Technology, Information and Internet
#J-18808-Ljbffr
Machine Learning Engineer, Personalization
role at
Whatnot .
This range is provided by Whatnot. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Compensation Base pay range:
$175,000.00/yr - $195,000.00/yr
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 or equity.
Company overview Whatnot
is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. We’re redefining 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, Ireland, Poland, and Germany, we’re building the future of online marketplaces—together. From fashion, beauty, and electronics to rare collectibles like trading cards, comic books, and even live plants, our live auctions have something for everyone. 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 our 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.
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
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 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.
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
Preferred Qualifications:
Experience building ML applications for Discovery and Personalization domains
Experience with backend development
Compensation 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 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.
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.
Seniority level Mid-Senior level
Employment type Full-time
Job function Engineering and Information Technology
Industries Technology, Information and Internet
#J-18808-Ljbffr