Machine Learning Research Jobs in New York
Machine Learning Research jobs in New York place candidates at the center of one of the most active markets in the country, with demand concentrated in finance, healthcare AI, media technology, and academic research at every level from junior researcher through principal scientist. The heaviest hiring is in New York City, with additional activity in Buffalo and Albany driven by university research programs and state-backed tech initiatives. Employers like JPMorgan Chase, Memorial Sloan Kettering Cancer Center, and IBM Research maintain a lasting presence here and recruit consistently for NLP, computer vision, and reinforcement learning specialties. Find a role that fits below and apply directly.
Find JobsOverview
Showing 5 of 10+ Machine Learning Research jobs
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
See All 10 Machine Learning Research Jobs in New York
Find roles in New York that match your experience and apply in just a few clicks.
Find JobsMachine Learning Research Jobs by City in New York
Where New York roles are concentrated, by current openings.
Machine Learning Research Job Market in New York
A snapshot from current New York openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Investment & Asset Management
- Science & Research
- Banking & Financial Services
- Consulting & Professional Services
What New York Employers Look For
The qualifications that appear most often in machine learning research jobs across New York.
- Master's or PhD in computer science, statistics, or a closely related field
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience designing and implementing large-scale machine learning models from scratch
- Published research, technical reports, or demonstrated contributions to open-source projects
- Familiarity with cloud computing environments including AWS, GCP, or Azure
- Strong written and verbal communication skills for cross-functional collaboration and publication
Machine Learning Research Jobs in New York: Frequently Asked Questions
How do you become a machine learning research in New York?
Most machine learning research roles in New York require at least a master's degree, with a PhD preferred for positions at research labs and academic institutions. New York does not issue a state license specific to machine learning research, so the path runs through education and demonstrated output: peer-reviewed publications, open-source contributions, or a strong graduate thesis. New York City's dense concentration of research labs, financial institutions, and university affiliates makes it one of the most accessible markets to break into at the research level.
Which companies hire machine learning researchs in New York?
Employers hiring machine learning researchs in New York right now include Achira, Apple, and Plaid, based on current listings on Migrate Mate as of September 2026. New York's mix of global financial firms, major academic medical centers, and established technology companies means demand cuts across industries rather than concentrating in a single sector.
Which New York cities have the most machine learning research jobs?
The cities with the most machine learning research openings in New York are New York. New York City dominates because of its density of financial services firms, media and advertising technology companies, and world-class research hospitals, while Buffalo and Albany draw activity from university research partnerships and state-supported technology development programs anchored by institutions like the University at Buffalo and SUNY Polytechnic Institute.
Are there remote machine learning research jobs in New York?
Yes, and more than most fields. About 63% of machine learning research openings tied to New York are remote or hybrid as of September 2026, reflecting the fact that the core work, model development, experimentation, and paper writing, is largely computer-based. Roles requiring access to proprietary data infrastructure or close lab collaboration are more likely to require on-site presence, while positions focused on modeling, analysis, and independent research tend to offer the most location flexibility.
How can I get hired as a machine learning research in New York with little or no experience?
The most realistic entry path is a research internship or PhD fellowship with a New York institution, since academic labs at Columbia, NYU, and Cornell Tech regularly take on graduate students and recent graduates for funded research positions. IBM Research and major financial firms like Two Sigma run structured research associate and residency programs that explicitly target candidates without full-time research experience. Building a public portfolio of reproducible experiments on platforms like GitHub and targeting applied scientist or junior research engineer titles, which feed into research roles, significantly improves a candidate's standing in New York's competitive market.
Where can I find and apply to machine learning research jobs in New York?
You can find and apply to machine learning research jobs in New York on Migrate Mate, which lists current New York openings updated regularly. Search the available roles, find the ones that match your background and target area, and apply directly to each employer through the listing.
See All 10 Machine Learning Research Jobs in New York
Find roles in New York that match your experience and apply in just a few clicks.
Find Jobs