Machine Learning Scientist, Whatnot
$180-230k
+ Equity
Live stream platform & marketplace
Job no longer available
Live stream platform & marketplace
1001+ employees
Job no longer available
$180-230k
+ Equity
1001+ employees
Company mission
To enable anyone to turn their passion into a business and bring people together through commerce.
Role
Who you are
- As our next Machine Learning Scientist you should have 4+ years of professional experience developing machine learning systems and algorithms,
- Bachelor’s degree in Computer Science, Statistics, Applied Mathematics, Economics, a related technical field, or equivalent work experience
- 1+ years of software or machine learning engineering experience building for consumer-scale loads
- Industry experience with a track record of applying the scientific methods to solve real-world problems on consumer scale data
- Experience leading work to develop and deploy machine learning- and data-based solutions in production
- Extensive experience with Python and SQL for data science, machine learning, and software development e.g. PyTorch, LightGBM, FastAPI
- Ability to work autonomously and lead initiatives across multiple product areas and communicate findings with leadership and product teams
- Comfortability with data warehouses and transformation tools such as Snowflake, dbt, Dagster
- Proficiency and experience in applied statistics and machine learning fields e.g. Experimentation and Causal Analysis, Recommendations, Fraud & Anomaly Detection, Natural Language Processing
- Professionalism around collaborating in a remote working environment and well tested reproducible work
- Above average documentation and communication skills
What the job involves
- We are looking for intellectually curious, entrepreneurial individuals to become foundational members of our Core Machine Learning team
- Bringing to bear a mixture of model development and software engineering skills, you will design, develop, and deploy models and scaled solutions to solve 0 to 1 problems across a wide variety of product surfaces
- The Core Machine Learning team architects design patterns while actively contributing to initiatives spanning search, recommendation, growth, trust and safety, and fraud, to name a few
- Develop and deploy new production machine learning algorithms and systems that enrich the buyer and seller experience
- Build and help set direction across the entire machine learning development process to implement production algorithms, including exploratory data analysis, data modeling, feature engineering, model training, testing, deployment, and monitoring
- Contribute across the data science and machine learning development stack: ideation, opportunity sizing, prototyping, load testing, deployment, and monitoring
- Drive initiatives across multiple product areas and communicate findings with leadership and product teams using dashboards, notebooks, and/or documents where appropriate
- Design and implement end-to-end data pipelines and systems that support MLOps and critical business processes
- Deep dive into mission-critical problems unique to Whatnot’s livestream auction ecosystem and design bespoke algorithmic solutions
Our take
Live shopping is changing the way people engage with eCommerce and Whatnot is one of the key platforms driving this shift. The company operates across the US, UK, and Europe, where millions of people connect each day to buy, sell, and build communities around shared interests.
Founded in 2019, Whatnot allows real-time auctions where buyers can watch sellers showcase products and share their expertise, creating a more interactive and personal shopper experience. Sellers include individual creators and small businesses who use live shows to reach audiences and grow their online presence.
As of 2025, the company reports over $6B in sales, with sellers earning significantly more on average than other major marketplaces. And with a range of investor support, Whatnot is committed to developing new ways to make online shopping more social and community-driven.
Steph
Company Specialist at Welcome to the Jungle
Meet the team
Jon Malkemus, VP Product Design
Insights
54% employee growth in 12 months
Company
Funding (last 2 of 8 rounds)
Oct 2025
$225m
SERIES F
Jan 2025
$265m
SERIES E
Total funding: $974.2m
Company benefits
- Wellness: Health, dental, vision, and life insurance plans. We also cover some of the cost for your dependents as well.
- Compensation: Generous compensation, including a competitive base salary and equity. Whatnot offers monthly reimbursement for internet and phone costs, along with a one-time home office set-up allowance. Whatnot offers a pension plan and matches employee contributions of up to 4% of the employee’s base salary.
- Recharge: Whatnot gives you the freedom to take time off as you see fit. And, we take company-wide Winter and Summer breaks so we can recharge. Whatnot provides a monthly allowance for wellness expenses. We know that to take care of our customers, we have to take care of ourselves. Supplemental health and life insurance coverage comes standard at Whatnot. 16 weeks of paid parental leave, and an additional one-month gradual return-to-work period.* Plus an additional childcare allowance, and a lifetime allowance for family planning, including adoption and fertility expenses. *The leave allowances provided by Whatnot may be dictated / informed by your country’s legal requirements,
- Flexibility: As a remote co-located team, we’re inspired by innovation and anchored in our values. With hubs in the US, UK, Germany, Ireland, and Poland, we’re building the future of online marketplaces –together.
Company values
- Always listen to customers
- Move uncomfortably fast
- Prioritize impact ruthlessly
- Own everything and nothing
- Set crazy goals
- Provide extreme transparency
- Optimize for the upside
- Team over ego
- Figure it out
- Deeply understand why
- Have fun & be kind
Company HQ
Venice, Los Angeles, CA
Articles
Leadership
Grant LaFontaine
(Co-Founder & CEO)Former Product Marketing Manager at Google, Project Manager at Facebook. Also co-founded Kit.
Logan Head
(Co-Founder & CTO)Experience in Engineering, including at Maker's Row, Factr, and Flight Club. Former Senior Product Manager at GOAT.
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