Machine Learning Engineer Jobs at Whatnot with Visa Sponsorship
Machine Learning Engineer jobs at Whatnot involve building 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 JobsJoin the Future of Commerce with Whatnot!
Whatnot is the largest live 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.
Compensation Range: $200K - $345K
Join the Future of Commerce with Whatnot!
Whatnot is the largest live 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.
Compensation Range: $200K - $345K
See all Machine Learning Engineer Jobs at Whatnot
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Engineer Jobs at Whatnot.
Get Access To All JobsTips for Finding Machine Learning Engineer Jobs at Whatnot
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.
Confirm sponsorship eligibility before applying
Whatnot sponsors H-1B, E-3, TN, F-1 OPT, F-1 CPT, J-1, and EB-2/EB-3 pathways. Check which category fits your nationality and status before your recruiter screen, so you can address eligibility directly rather than waiting for the offer stage.
Time your OPT application around Whatnot's hiring cycles
If you're on F-1 OPT, the 90-day unemployment limit is unforgiving. Target Whatnot's ML roles when your OPT start date gives you a realistic runway to complete their technical interview loop, which typically spans several weeks.
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.
Frequently 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 visa, TN visa, F-1 OPT, F-1 CPT, J-1 visa, and permanent residence pathways including EB-2 and EB-3. Australian citizens are eligible for the E-3 visa, which bypasses the H-1B lottery entirely. Canadian and Mexican nationals in qualifying ML occupations may be eligible for TN visa 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.