Remote Machine Learning Research Jobs
Remote Machine Learning Research jobs are open across the U.S. in AI research, applied science, and deep learning, with opportunities at remote-first labs, technology companies, and research-driven organizations ranging from early-career roles to principal researcher positions. Employers actively hiring remotely include Rad AI, Whatnot, and Deepgram. See the openings below and apply to the ones that match your experience.
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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
Lead research projects across the marketplace dynamics problem area: simulation, auction and allocation mechanics, long-term objective modeling, exploration and information value, or marketplace experimentation methods
Take ideas from hypothesis to production: literature review, prototyping, offline validation, shadow testing, and online experiments shipped through partner teams in Discovery and the Seller org
Build models of how the marketplace behaves as a system: learned simulators that predict segment-level effects of ranking and policy changes, and surrogate models of long-term marketplace outcomes
Model Whatnot's actual market mechanics: auction and bidding dynamics, and discovery exposure allocation as a portfolio problem, including allocation to rising sellers
Advance how a multi-sided live marketplace evaluates changes: off-policy evaluation, switchback and interference-robust experiment designs, and variance reduction
Contribute to Whatnot's external technical presence through publications, open-source work, and public benchmarks
NYC Based:
Team members in this role are required to be within commuting distance (50 miles) of our New York City hub.
You
Curious about who thrives at Whatnot? We’ve found that embodying a low ego, growth mindset, and high-impact drive goes a long way here. As our next Machine Learning Engineer you should have:
5+ years of industry experience building and deploying ML models to solve user problems at scale
Depth in at least one of: recommendation systems, causal inference, off-policy evaluation, reinforcement learning and bandits, auction or mechanism design, or marketplace experimentation
A track record of applying scientific methods to solve real-world problems on consumer-scale data
Advanced proficiency in Python, SQL, and common ML frameworks like PyTorch, XGBoost, etc
Strong grounding in applied statistics, experiment design and theoretical machine learning
Strong communication and leadership skills; ability to influence roadmaps and align cross-functional teams in a remote environment
Preferred Qualifications:
Experience in two-sided marketplaces, ads and auction systems, or pricing
Experience building simulators or economic models of platform behavior
Compensation
For Full-Time (Salary) US-based applicants: $207,000/year to $290,000X/year + benefits + equity.
The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.
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
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.
Please note: Whatnot will only contact you through official @whatnot.com email addresses. If you see an email impersonating a Whatnot recruiter, please disregard and report it as spam.
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: $207K - $290K
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
Lead research projects across the marketplace dynamics problem area: simulation, auction and allocation mechanics, long-term objective modeling, exploration and information value, or marketplace experimentation methods
Take ideas from hypothesis to production: literature review, prototyping, offline validation, shadow testing, and online experiments shipped through partner teams in Discovery and the Seller org
Build models of how the marketplace behaves as a system: learned simulators that predict segment-level effects of ranking and policy changes, and surrogate models of long-term marketplace outcomes
Model Whatnot's actual market mechanics: auction and bidding dynamics, and discovery exposure allocation as a portfolio problem, including allocation to rising sellers
Advance how a multi-sided live marketplace evaluates changes: off-policy evaluation, switchback and interference-robust experiment designs, and variance reduction
Contribute to Whatnot's external technical presence through publications, open-source work, and public benchmarks
NYC Based:
Team members in this role are required to be within commuting distance (50 miles) of our New York City hub.
You
Curious about who thrives at Whatnot? We’ve found that embodying a low ego, growth mindset, and high-impact drive goes a long way here. As our next Machine Learning Engineer you should have:
5+ years of industry experience building and deploying ML models to solve user problems at scale
Depth in at least one of: recommendation systems, causal inference, off-policy evaluation, reinforcement learning and bandits, auction or mechanism design, or marketplace experimentation
A track record of applying scientific methods to solve real-world problems on consumer-scale data
Advanced proficiency in Python, SQL, and common ML frameworks like PyTorch, XGBoost, etc
Strong grounding in applied statistics, experiment design and theoretical machine learning
Strong communication and leadership skills; ability to influence roadmaps and align cross-functional teams in a remote environment
Preferred Qualifications:
Experience in two-sided marketplaces, ads and auction systems, or pricing
Experience building simulators or economic models of platform behavior
Compensation
For Full-Time (Salary) US-based applicants: $207,000/year to $290,000X/year + benefits + equity.
The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.
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
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.
Please note: Whatnot will only contact you through official @whatnot.com email addresses. If you see an email impersonating a Whatnot recruiter, please disregard and report it as spam.
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: $207K - $290K
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Who's Hiring
Top Industries Hiring
- Biotechnology & Pharmaceuticals
- Fintech
- Staffing & Recruiting
- Technology & Software
- Investment & Asset Management
What Employers Look For
The qualifications that appear most often in remote machine learning research jobs.
- PhD or MS in computer science, statistics, or a related quantitative field
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience designing and running controlled experiments on large-scale datasets
- Published or peer-reviewed research in a relevant machine learning subfield
- Ability to implement and evaluate state-of-the-art models from recent literature
- Strong written and verbal communication skills for presenting research findings internally
Tips for Your Remote Machine Learning Research Job Search
Apply early to remote roles that fit
Migrate Mate lists remote machine learning research openings from across the U.S. in one place. Search by role and apply directly to the positions that match your background without sorting through listings mixed with on-site roles.
Build a public research portfolio
Remote employers can't observe your process in person, so your visible output does the talking. Publish reproducible experiments, contribute to open-source machine learning projects, and document your methodology clearly so hiring teams can evaluate your thinking before the first conversation.
Sharpen your async written communication
Remote research teams run on written handoffs, design documents, and experiment logs. Practice writing concise, well-structured research updates and decision summaries. Strong async communication signals that you'll integrate into a distributed team without requiring constant check-ins.
Target remote-first organizations specifically
Companies built around distributed teams have established onboarding, tooling, and collaboration norms for remote researchers. Prioritize roles at remote-first AI labs and fully distributed product organizations, where remote work is the default rather than an exception made for a single hire.
Remote Machine Learning Research Jobs: Frequently Asked Questions
How do I get a remote machine learning research job?
Target companies with fully distributed research teams or remote-first cultures, since they have the infrastructure and norms to support independent research work. Remote employers screen for strong written communication, the ability to document experiments clearly, and self-directed project management. A public research portfolio, open-source contributions, or published work gives you a concrete edge over candidates with equivalent credentials but no visible output.
Which companies hire remote machine learning researchs?
Companies hiring remote machine learning researchs right now include Rad AI, Whatnot, and Deepgram, based on current remote listings on Migrate Mate as of September 2026. Remote-first AI labs, distributed product teams at technology companies, and research arms of enterprise software organizations are the most consistent sources of fully remote machine learning research roles.
Can you get a remote machine learning research job with no experience?
Yes, but remote entry-level research roles are harder to land because employers expect you to make progress independently without close supervision. Your best path is contributing to open-source machine learning projects, publishing reproducible experiments on public platforms, or completing research-track graduate coursework with visible outputs. Remote-first companies and smaller AI startups are more likely to hire entry-level candidates who demonstrate initiative through real, documented work.
Do you need a degree for remote machine learning research jobs?
Usually, but the weight placed on formal credentials varies by employer. Most research roles at established labs and larger companies expect a graduate degree in machine learning, computer science, or a related field. Remote-first startups and applied research teams are more willing to evaluate candidates on published work, GitHub contributions, and demonstrated research outcomes when those outputs are strong enough to stand on their own.
Which industries hire the most remote machine learning researchs?
Most remote machine learning research openings sit in Biotechnology & Pharmaceuticals, Fintech, and Staffing & Recruiting, per current remote listings on Migrate Mate as of September 2026. These sectors rely on distributed research teams because the work is computationally driven, documentation-heavy, and well-suited to asynchronous collaboration across time zones.
See All 11 Remote Machine Learning Research Jobs
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