AI ML Engineering Jobs at Whatnot with Visa Sponsorship
Whatnot builds its AI and machine learning infrastructure on engineers who can work across recommendation systems, trust and safety models, and real-time bidding pipelines. The company has a consistent track record of sponsoring work visas for this function, supporting candidates from application through to long-term status.
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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 26+ AI ML Engineering at Whatnot jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI ML Engineering at Whatnot roles.
Get Access To All JobsTips for Finding AI ML Engineering Jobs at Whatnot Jobs
Frame your ML work around commerce problems
Whatnot's AI team focuses on live commerce, so framing your experience around recommendation engines, fraud detection, or dynamic pricing signals directly to recruiters that you understand the product. Generic ML credentials get screened out faster.
Use Migrate Mate to identify active AI ML openings
Whatnot's AI ML Engineering roles aren't always listed under a single job title. Use Migrate Mate to filter for sponsorship-confirmed openings at Whatnot and surface roles across ML, data science, and applied research that match your background.
Prepare specialty occupation documentation early
For H-1B petitions, USCIS scrutinizes whether the role genuinely requires a specialized degree. Collect transcripts, degree equivalency letters if your credential is from outside the U.S., and any prior approval notices before your employer files the I-129.
Align your start date with H-1B cap timing
If your offer depends on winning the H-1B lottery, the October 1 cap-subject start date is fixed. Build that constraint into your offer negotiation early so Whatnot's legal team can plan the LCA filing and DOL certification timeline without last-minute pressure.
AI ML Engineering at Whatnot jobs are hiring across the US. Find yours.
Find AI ML Engineering at Whatnot JobsFrequently Asked Questions
Does Whatnot sponsor H-1B visas for AI ML Engineers?
Yes, Whatnot sponsors H-1B visas for AI ML Engineering roles. The company works with immigration counsel to file the Labor Condition Application with the DOL and the I-129 petition with USCIS. Cap-subject candidates should factor in the April lottery registration window and the October 1 start date when planning their timeline.
How do I apply for AI ML Engineering jobs at Whatnot?
Applications go through Whatnot's careers page, where roles are listed by team and function. AI ML Engineering positions often appear under titles like Machine Learning Engineer, Applied Scientist, or Recommendation Systems Engineer, so searching broadly across those categories helps. Migrate Mate also surfaces sponsorship-confirmed Whatnot openings, which can help you identify roles that are actively accepting international applicants.
Which visa types does Whatnot commonly use for AI ML Engineering roles?
Whatnot sponsors H-1B, E-3, TN, F-1 OPT, F-1 CPT, and J-1 visas for this function, and supports EB-2 and EB-3 Green Card pathways for longer-term employees. The right visa depends on your nationality and current status. Australian citizens have access to the E-3, which avoids the H-1B lottery entirely and can be processed at a U.S. consulate in a matter of weeks.
What qualifications does Whatnot expect for AI ML Engineering roles?
Most AI ML Engineering roles at Whatnot require a bachelor's degree or higher in computer science, statistics, or a closely related field, along with hands-on experience building production ML systems. Roles focused on live commerce infrastructure often prioritize work in recommendation systems, real-time model serving, or trust and safety. A graduate degree can strengthen a profile for senior or research-oriented positions, and it also supports a stronger specialty occupation argument in H-1B filings.
How do I plan my visa timeline when joining Whatnot as an AI ML Engineer?
Timeline depends on your visa type. E-3 and TN processing at a consulate can move in a few weeks. H-1B cap-subject filings require a registration in March, approval by late spring, and a start date no earlier than October 1. If you're transferring an existing H-1B, Whatnot can file a portability petition and you can start before approval. Confirm your current status and authorized period with your employer's immigration counsel before accepting an offer.
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