Machine Learning Jobs at Whatnot with Visa Sponsorship
Whatnot builds its machine learning function around recommendation systems, fraud detection, and real-time auction personalization. The company has a consistent track record of sponsoring international talent across multiple visa categories for ML roles, making it a viable target if you're navigating work authorization in the U.S.
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Get Access To All JobsLocation
San Francisco, CA; Los Angeles, CA; New York, NY; Seattle, WA
Employment Type
Full time
Department
Engineering
Compensation
$190K – $300K • Offers Equity
The salary or hourly rate range may be inclusive of several levels that would be applicable to the position. Final salary or hourly rate will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary or hourly rate, not benefits or equity.
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.
Role
We’re looking for builders–intellectually curious, highly entrepreneurial engineers eager to shape the future of AI and ML at Whatnot. You’ll design and scale the core infrastructure that powers machine learning and self-hosted large language model applications across the company, working side by side with machine learning scientists to bring cutting-edge models into production and unlock entirely new product experiences. This means building systems that make advanced ML dependable and fast at scale–from low-latency, large model serving to distributed training & high-throughput GPU inference.
What you'll do:
- Own the infrastructure powering AI and ML models across critical business surfaces–supporting growth, recommendations, trust and safety, fraud, seller tooling, and more.
- Prototype, deploy, and productionalize novel ML architectures that directly shape user experience and marketplace dynamics.
- Design and scale inference infrastructure capable of serving large models with low latency and high throughput.
- Build distributed training and inference pipelines leveraging GPUs and both model and data parallelism.
- Stretch beyond your comfort zone to take on new technical challenges as we scale AI across Whatnot’s ecosystem.
US Based: 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 New York, Seattle, Los Angeles, and San Francisco hubs.
You
People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it.
As our next AI/ML Platform Engineer you should have 4+ years of professional experience developing machine learning systems and algorithms, plus:
- Bachelor’s degree in Computer Science, Statistics, Applied Mathematics or a related technical field, or equivalent work experience.
- 3+ years of software engineering experience building and maintaining production systems for consumer-scale loads.
- 1+ years of professional experience developing software in Python.
- Ability to work autonomously and drive initiatives across multiple product areas and communicate findings with leadership and product teams.
- Experience with operational, search, and key-value databases such as PostgreSQL, DynamoDB, Elasticsearch, Redis.
- Firm grasp of visualization tools for monitoring and logging e.g. DataDog, Grafana.
- Familiarity with cloud computing platforms and managed services such as AWS Sagemaker, Lambda, Kinesis, S3, EC2, EKS/ECS, Apache Kafka, Flink.
- Professionalism around collaborating in a remote working environment and well tested, reproducible work.
- Exceptional documentation and communication skills.
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.
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.
Location
San Francisco, CA; Los Angeles, CA; New York, NY; Seattle, WA
Employment Type
Full time
Department
Engineering
Compensation
$190K – $300K • Offers Equity
The salary or hourly rate range may be inclusive of several levels that would be applicable to the position. Final salary or hourly rate will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary or hourly rate, not benefits or equity.
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.
Role
We’re looking for builders–intellectually curious, highly entrepreneurial engineers eager to shape the future of AI and ML at Whatnot. You’ll design and scale the core infrastructure that powers machine learning and self-hosted large language model applications across the company, working side by side with machine learning scientists to bring cutting-edge models into production and unlock entirely new product experiences. This means building systems that make advanced ML dependable and fast at scale–from low-latency, large model serving to distributed training & high-throughput GPU inference.
What you'll do:
- Own the infrastructure powering AI and ML models across critical business surfaces–supporting growth, recommendations, trust and safety, fraud, seller tooling, and more.
- Prototype, deploy, and productionalize novel ML architectures that directly shape user experience and marketplace dynamics.
- Design and scale inference infrastructure capable of serving large models with low latency and high throughput.
- Build distributed training and inference pipelines leveraging GPUs and both model and data parallelism.
- Stretch beyond your comfort zone to take on new technical challenges as we scale AI across Whatnot’s ecosystem.
US Based: 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 New York, Seattle, Los Angeles, and San Francisco hubs.
You
People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it.
As our next AI/ML Platform Engineer you should have 4+ years of professional experience developing machine learning systems and algorithms, plus:
- Bachelor’s degree in Computer Science, Statistics, Applied Mathematics or a related technical field, or equivalent work experience.
- 3+ years of software engineering experience building and maintaining production systems for consumer-scale loads.
- 1+ years of professional experience developing software in Python.
- Ability to work autonomously and drive initiatives across multiple product areas and communicate findings with leadership and product teams.
- Experience with operational, search, and key-value databases such as PostgreSQL, DynamoDB, Elasticsearch, Redis.
- Firm grasp of visualization tools for monitoring and logging e.g. DataDog, Grafana.
- Familiarity with cloud computing platforms and managed services such as AWS Sagemaker, Lambda, Kinesis, S3, EC2, EKS/ECS, Apache Kafka, Flink.
- Professionalism around collaborating in a remote working environment and well tested, reproducible work.
- Exceptional documentation and communication skills.
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.
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 at Whatnot jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning at Whatnot roles.
Get Access To All JobsTips for Finding Machine Learning Jobs at Whatnot Jobs
Frame Your ML Work Around Commerce Problems
Whatnot's ML team focuses on live-commerce challenges like bid prediction, seller ranking, and content recommendation. Tailor your portfolio and resume to show experience with real-time inference, ranking systems, or fraud detection rather than general research.
Target Roles That Align With Your Degree Field
H-1B and E-3 petitions for ML roles require the position to qualify as a specialty occupation tied to your specific degree. A computer science or statistics background maps cleanly, but an unrelated degree with no direct ML coursework can create USCIS scrutiny at offer stage.
Get Your LCA Timing Right After Accepting an Offer
Your employer must file a Labor Condition Application with the DOL before submitting your H-1B or E-3 petition. LCA certification typically takes seven business days. Build that window into your expected start date conversation during offer negotiation so nothing slips.
Use Migrate Mate to Identify Open ML Positions
Whatnot's ML hiring spans multiple specializations and seniority levels at any given time. Use Migrate Mate to filter open machine learning roles at Whatnot by visa type and see which positions are currently active before investing time in outreach or applications.
Prepare for a Technical Bar That Reflects Production Scale
Whatnot's interview process for ML roles tests both modeling depth and systems thinking, since models run against live auction traffic at scale. Brush up on online learning, low-latency serving, and A/B experimentation frameworks before your technical rounds.
Machine Learning at Whatnot jobs are hiring across the US. Find yours.
Find Machine Learning at Whatnot JobsFrequently Asked Questions
Does Whatnot sponsor H-1B visas for Machine Learning roles?
Yes, Whatnot sponsors H-1B visas for machine learning positions. The company has an established pattern of filing H-1B petitions for technical roles, and ML positions typically qualify as specialty occupations under USCIS criteria given their degree requirements in computer science, statistics, or a related field. Sponsorship is handled directly by Whatnot's internal people operations team.
How do I apply for Machine Learning jobs at Whatnot?
Apply directly through Whatnot's careers page, where ML roles are listed by team focus and seniority. You can also browse and filter current openings on Migrate Mate, which surfaces Whatnot's visa-sponsoring ML positions alongside sponsorship details. The application process typically includes a recruiter screen, a technical assessment, and several rounds of system design and modeling interviews.
Which visa types does Whatnot commonly sponsor for Machine Learning positions?
Whatnot sponsors a broad range of visa categories for ML roles, including H-1B, E-3 (for Australian nationals), TN (for Canadian and Mexican nationals), F-1 OPT and CPT, J-1, and employment-based Green Cards through the EB-2 and EB-3 pathways. The right category depends on your nationality, educational background, and where you are in your immigration journey.
What qualifications does Whatnot expect for Machine Learning roles?
Whatnot's ML roles generally require a bachelor's degree or higher in computer science, statistics, or a closely related field, with hands-on experience building and deploying production models. Senior roles typically expect familiarity with recommendation systems, real-time ranking, or fraud detection at scale. Research experience or publications can strengthen your profile for more senior positions, but applied engineering depth carries significant weight given the live-commerce context.
How do I time my application if I'm on F-1 OPT and targeting a Whatnot ML role?
If you're on standard F-1 OPT, you have 12 months of work authorization, extendable to 36 months with a STEM OPT extension if your degree qualifies. H-1B cap-subject filings open in March each year for an October 1 start date. Coordinate your application timeline so that an offer and onboarding fall within your remaining OPT window, leaving enough runway for USCIS to process the H-1B petition if you're selected in the lottery.
See which Machine Learning at Whatnot employers are hiring and sponsoring visas right now.
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