ML Research Engineer Jobs
ML Research Engineer jobs are open across technology, healthcare, finance, and defense, from new-grad to staff and principal level, with specializations in foundation models, reinforcement learning, and computer vision. Find a role that fits from the openings below and apply directly.
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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
ML Research Engineer Jobs by Experience Level
Top Cities Hiring ML Research Engineers
Explore ML research engineer openings in the cities hiring most right now.
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Find ML Research Engineer JobsML Research Engineer Job Market
Who's Hiring
- Apple26
- Scale AI17
- ByteDance6
- Meta5
- Achira5A
Top Industries Hiring
- Technology & Software23
- Electronics & Hardware14
- Artificial Intelligence12
- Banking & Financial Services6
- Investment & Asset Management5
What Employers Look For
The qualifications that appear most often in ML research engineer jobs.
- Advanced degree in machine learning, computer science, or a closely related field
- Proficiency in Python and deep learning frameworks such as PyTorch or JAX
- Experience designing, training, and evaluating large-scale neural network models
- Publication record or demonstrated original research contributions in ML or AI
- Strong mathematical foundation in statistics, linear algebra, and optimization
- Experience with distributed training, cloud compute platforms, or MLOps tooling
Tips for Your ML Research Engineer Job Search
Tailor your resume to the research stack
List the specific frameworks you've used in production or published research, PyTorch, JAX, or TensorFlow, alongside your model architectures. Hiring managers scan for these before reading your experience bullets, so front-load them in a skills or technical summary section.
Link publications and open-source contributions
Attach a Google Scholar profile or GitHub repository to every application. ML research teams weigh published papers and reproducible code heavily, and a single first-author paper at a top venue can move you past the resume screen faster than years of industry experience alone.
Apply early to roles that fit
Migrate Mate lists ml research engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter by research versus applied focus
Job titles blur the line between pure research and applied engineering. Read each listing for keywords like 'publish,' 'novel methods,' or 'production serving.' Targeting roles that match your actual focus, foundational versus deployment, improves your interview fit and reduces mismatched offers.
Prepare a research talk, not just a portfolio
Most ML research engineer loops include a technical presentation on your own work. Practice explaining your problem setup, baselines, ablations, and results in 20 minutes. Teams evaluate how you reason about failure modes, not just whether your final numbers were strong.
Negotiate compute resources alongside compensation
GPU cluster access, cloud compute budgets, and dataset licensing rights affect your ability to do the job. Raise these in the offer stage alongside salary. Teams that can't answer concretely often signal a mismatch between the research mandate and actual infrastructure investment.
ML Research Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most ml research engineers?
The companies hiring the most ml research engineers right now include Apple, Scale AI, and ByteDance, with the largest share of openings in California, Washington, and New York, based on current listings on Migrate Mate as of September 2026. Demand is concentrated at large technology companies and well-funded AI labs, though defense contractors and healthcare AI startups have expanded hiring meaningfully in recent cycles.
How many ml research engineer jobs are remote?
About 34% of ml research engineer openings are fully remote or hybrid as of September 2026, reflecting strong demand from teams that operate across distributed research centers. Roles focused on language modeling and data-centric AI tend to offer the most remote flexibility, while positions requiring access to proprietary hardware clusters or on-site collaboration with product teams are more likely to require in-person presence.
How do you become a ml research engineer?
Start by building a strong foundation in mathematics, particularly linear algebra, probability, and calculus, alongside proficiency in Python and a major deep learning framework. Complete graduate-level coursework or a master's or doctoral program in machine learning or computer science. Contribute to open-source projects, replicate published papers, and aim to publish or present original work. Internships at research labs or AI teams convert directly into full-time roles and are often the most direct path in.
Can you get hired as a ml research engineer without much experience?
Yes, though the bar is high without a graduate degree or publications. The most effective entry points are research internships during a master's or doctoral program, open-source contributions to widely used ML libraries, and strong performance in research-adjacent roles such as data scientist or ML engineer. Replicating landmark papers with novel extensions and sharing results publicly demonstrates research capability in the absence of a formal publication record.
What does the ml research engineer interview process look like?
Most loops include a recruiter screen, a coding round focused on data structures and ML fundamentals, a research discussion where you walk through a past project in depth, and a technical presentation on original work. Some teams add a take-home research problem or a whiteboard session on model design and experimental methodology. Final rounds typically involve senior researchers evaluating your ability to scope a research problem and reason clearly about tradeoffs.
Where can I find and apply to ml research engineer jobs?
You can find and apply to ml research engineer jobs on Migrate Mate, which lists current openings from across the United States in one place. Search the listings to find roles that match your focus area and experience level, then apply directly to each listing that fits.
See All 139+ ML Research Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find ML Research Engineer Jobs