Machine Learning Engineer Jobs at Whatnot with Visa Sponsorship
Whatnot's machine learning team builds the recommendation systems, pricing models, and real-time ranking infrastructure that power a live commerce platform at scale. The company has a consistent track record of sponsoring international engineers across multiple visa categories, making it a realistic target for ML engineers who need work authorization.
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Get Access To All Jobsđ Join the Future of Commerce with Whatnot!
Whatnot is the largest livestream 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.
đ» Role
- Design, train, and deploy both traditional ML and LLM-powered models to detect fraudulent behaviors across users, payments, and marketplace interactions.
- Lead the end-to-end architecture of fraud detection, prevention, and intervention systems â balancing platform security with a seamless user experience.
- Build intelligent user graphs to model behavioral patterns, collusion networks, and account connectivity.
- Develop scalable data pipelines and real-time inference systems supporting high-volume, low-latency ML workloads.
- Conduct deep behavioral and adversarial data analysis to uncover fraud trends and continuously improve detection accuracy.
- Partner cross-functionally with Trust & Safety, Payments, and Infrastructure teams to develop features, labels, and model evaluation pipelines.
- Implement model monitoring and drift detection systems to ensure reliability and responsiveness.
- Contribute to fraud risk orchestration, combining rules, models, and heuristics for decision automation.
- Define and track key metrics and dashboards for fraud detection effectiveness (e.g., precision, recall, false-positive rate, latency).
- Stay ahead of emerging fraud tactics and continuously translate insights into adaptive, production-ready systems.
We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our SF, NYC, LA OR SEA hubs.
đ You
Curious about who thrives at Whatnot? Weâve found that embodying a low ego, growth mindset, and high-impact drive goes a long way here.
- Bachelorâs degree in Computer Science, a related field, or equivalent work experience.
- 2â6 years of experience in machine learning or software engineering, ideally in risk, fraud, or trust & safety domains.
- Strong proficiency in Python and ML libraries (e.g., scikit-learn, PyTorch, LightGBM).
- Solid backend development skills and experience deploying ML models to production (batch or real-time).
- Experience in data analysis and ETL (SQL, Spark, DBT) for data pipeline building.
- Familiarity with fraud detection techniques such as chargeback prediction, anomaly detection, or graph-based modeling.
- Experience with data orchestration frameworks (Dagster, Kubeflow) and feature store design.
- Ability to translate business risk into measurable ML solutions and collaborate across diverse teams.
đ Benefits
- Generous Holiday and Time off Policy
- 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.
đ 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.
đ Join the Future of Commerce with Whatnot!
Whatnot is the largest livestream 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.
đ» Role
- Design, train, and deploy both traditional ML and LLM-powered models to detect fraudulent behaviors across users, payments, and marketplace interactions.
- Lead the end-to-end architecture of fraud detection, prevention, and intervention systems â balancing platform security with a seamless user experience.
- Build intelligent user graphs to model behavioral patterns, collusion networks, and account connectivity.
- Develop scalable data pipelines and real-time inference systems supporting high-volume, low-latency ML workloads.
- Conduct deep behavioral and adversarial data analysis to uncover fraud trends and continuously improve detection accuracy.
- Partner cross-functionally with Trust & Safety, Payments, and Infrastructure teams to develop features, labels, and model evaluation pipelines.
- Implement model monitoring and drift detection systems to ensure reliability and responsiveness.
- Contribute to fraud risk orchestration, combining rules, models, and heuristics for decision automation.
- Define and track key metrics and dashboards for fraud detection effectiveness (e.g., precision, recall, false-positive rate, latency).
- Stay ahead of emerging fraud tactics and continuously translate insights into adaptive, production-ready systems.
We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our SF, NYC, LA OR SEA hubs.
đ You
Curious about who thrives at Whatnot? Weâve found that embodying a low ego, growth mindset, and high-impact drive goes a long way here.
- Bachelorâs degree in Computer Science, a related field, or equivalent work experience.
- 2â6 years of experience in machine learning or software engineering, ideally in risk, fraud, or trust & safety domains.
- Strong proficiency in Python and ML libraries (e.g., scikit-learn, PyTorch, LightGBM).
- Solid backend development skills and experience deploying ML models to production (batch or real-time).
- Experience in data analysis and ETL (SQL, Spark, DBT) for data pipeline building.
- Familiarity with fraud detection techniques such as chargeback prediction, anomaly detection, or graph-based modeling.
- Experience with data orchestration frameworks (Dagster, Kubeflow) and feature store design.
- Ability to translate business risk into measurable ML solutions and collaborate across diverse teams.
đ Benefits
- Generous Holiday and Time off Policy
- 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.
đ 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.
See all 32+ Machine Learning Engineer at Whatnot jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Engineer at Whatnot roles.
Get Access To All JobsTips for Finding Machine Learning Engineer Jobs at Whatnot Jobs
Tailor your portfolio to live commerce ML
Whatnot's ML problems center on real-time recommendations, dynamic pricing, and auction ranking under latency constraints. Projects demonstrating experience with streaming data pipelines or online learning systems will resonate more than offline batch modeling work.
Clarify H-1B transfer versus new petition at offer stage
If you're already on an approved H-1B, Whatnot can file a transfer petition rather than waiting for the annual lottery. Raise your current status and priority date with the recruiting team during offer negotiation so USCIS paperwork doesn't delay your start date.
Prepare documentation proving specialty occupation for ML
USCIS scrutinizes ML roles to confirm a bachelor's degree in a specific technical field is a genuine requirement. Gather transcripts, degree certificates, and any postgraduate credentials before your offer stage so Whatnot's immigration counsel can build a clean H-1B or E-3 petition quickly.
Use Migrate Mate to identify open ML roles at Whatnot
Filter by visa type on Migrate Mate to surface Whatnot's active Machine Learning Engineer listings alongside the sponsorship categories they support. Applying through a targeted list saves time compared to manually tracking a live commerce company's rapidly changing job postings.
Machine Learning Engineer at Whatnot jobs are hiring across the US. Find yours.
Find Machine Learning Engineer at Whatnot JobsFrequently Asked Questions
Does Whatnot sponsor H-1B visas for Machine Learning Engineers?
Yes, Whatnot sponsors H-1B visas for Machine Learning Engineers. If you're already on an H-1B with another employer, Whatnot can file a transfer petition and you can begin work as soon as USCIS receives it, without waiting for the April lottery. New H-1B registrations are subject to the annual cap and lottery, typically held in March for an October 1 start date.
How do I apply for Machine Learning Engineer jobs at Whatnot?
Browse Whatnot's active Machine Learning Engineer openings on Migrate Mate, where listings are filtered by visa sponsorship type so you can confirm your category is supported before applying. Submit your application through Whatnot's careers portal with a resume that highlights real-time systems, recommendation modeling, or marketplace ML experience, since those map directly to Whatnot's core platform challenges.
Which visa types does Whatnot sponsor for Machine Learning Engineer roles?
Whatnot sponsors H-1B, E-3, TN, F-1 OPT, F-1 CPT, J-1, and permanent residence pathways including EB-2 and EB-3. Australian citizens are eligible for the E-3, which bypasses the H-1B lottery entirely. Canadian and Mexican nationals in qualifying ML occupations may be eligible for TN status, which can be obtained at a port of entry without a USCIS petition.
What qualifications does Whatnot expect from Machine Learning Engineer candidates?
Whatnot's ML roles typically require a bachelor's or graduate degree in computer science, statistics, or a closely related field, plus hands-on experience building and deploying models in production environments. Familiarity with recommendation systems, auction mechanics, or real-time ranking is a practical advantage given Whatnot's live commerce infrastructure. Strong Python skills and experience with large-scale data pipelines are expected across most levels.
How long does the H-1B sponsorship process take at a company like Whatnot?
If you're transferring from an existing H-1B, you can typically start within a few weeks of USCIS receiving the petition. For new cap-subject petitions, the timeline runs from March registration through an October 1 start date at the earliest. USCIS premium processing, which Whatnot may elect to use, reduces adjudication time to 15 business days but doesn't affect the October start date for cap-subject cases.
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