Machine Learning Research Jobs
Machine Learning Research jobs are open across technology, healthcare, finance, and defense, from research scientist to principal researcher and research director, with specializations in deep learning, natural language processing, and computer vision. Find a role that fits from the openings below and apply directly.
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Showing 5 of 163+ Machine Learning Research jobs
About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the flexibility to do your best work. Creating a career you love? It's Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
At Pinterest Labs, you'll work on tackling new challenges in machine learning and multi-modal large language models along with a world-class team of research scientists, and machine learning engineers. You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: natural language processing (NLP) and reasoning capability, computer vision for multi-modality, graph neural network, inclusive and responsible AI, reinforcement learning, user modeling, and recommender systems.
What you'll do:
- Contribute to cutting-edge research in machine learning and LLM that can be applied to Pinterest problems, especially search agent, recommendation agent, reason and planning agent
- Collect, analyze, and synthesize findings from data and build intelligent data-driven model
- Write clean, efficient, and sustainable code
- Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across growth, discovery, ads and search
- Scope and independently solve moderately complex problems
What we're looking for:
- MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field
- 6+ years of industry experience
- Experience in machine learning/information retrieval
- Mastery of at least one systems languages (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)
- Experience in research and in solving analytical problems
- Cross-functional collaborator and strong communicator
- Comfortable solving ambiguous problems and adapting to a dynamic environment
In-Office Requirement Statement:
- We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
- This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
#LI-REMOTE
#LI-DM57
Our Commitment to Inclusion:
About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the flexibility to do your best work. Creating a career you love? It's Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
At Pinterest Labs, you'll work on tackling new challenges in machine learning and multi-modal large language models along with a world-class team of research scientists, and machine learning engineers. You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: natural language processing (NLP) and reasoning capability, computer vision for multi-modality, graph neural network, inclusive and responsible AI, reinforcement learning, user modeling, and recommender systems.
What you'll do:
- Contribute to cutting-edge research in machine learning and LLM that can be applied to Pinterest problems, especially search agent, recommendation agent, reason and planning agent
- Collect, analyze, and synthesize findings from data and build intelligent data-driven model
- Write clean, efficient, and sustainable code
- Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across growth, discovery, ads and search
- Scope and independently solve moderately complex problems
What we're looking for:
- MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field
- 6+ years of industry experience
- Experience in machine learning/information retrieval
- Mastery of at least one systems languages (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)
- Experience in research and in solving analytical problems
- Cross-functional collaborator and strong communicator
- Comfortable solving ambiguous problems and adapting to a dynamic environment
In-Office Requirement Statement:
- We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
- This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
#LI-REMOTE
#LI-DM57
Our Commitment to Inclusion:
Machine Learning Research Jobs by Experience Level
Top Cities Hiring Machine Learning Researchs
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Find JobsMachine Learning Research Job Market
Who's Hiring
- Apple32
- Scale AI23
- Achira5A
- Nuro4
- Exponent4
Top Industries Hiring
- Technology & Software29
- Artificial Intelligence27
- Electronics & Hardware21
- Investment & Asset Management10
- Banking & Financial Services5
What Employers Look For
The qualifications that appear most often in 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 Machine Learning Research Job Search
Lead with reproducible research outputs
Your resume should link to public repositories, preprints, or published papers so hiring teams can verify your work. Listing model names or benchmark scores without evidence won't move you past an initial screening for a research role.
Apply early to roles that fit
Migrate Mate lists machine learning research openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter openings by research stage focus
Some teams want applied researchers who ship models to production, while others want fundamental researchers who write papers. Read job descriptions carefully for phrases like 'product impact' versus 'novel contributions' to avoid applying to roles that don't match your actual work style.
Tailor your PhD or postdoc framing carefully
Industry hiring managers value academic credentials but worry about translation to shipping timelines. Frame dissertation work around the problem you solved and its practical scope, not the methodological novelty, so it reads as relevant to a product-adjacent research team.
Prepare a research presentation for onsite rounds
Most machine learning research onsites include a whiteboard or slide presentation of a past project. Choose a paper or project where you made a non-obvious design decision, because interviewers probe trade-offs, not just results.
Negotiate compute and publication rights separately
Salary negotiation in research roles often matters less than access to GPU clusters and the company's policy on publishing findings. Clarify publication approval timelines and compute allocation during the offer stage, not after you've accepted.
Machine Learning Research Jobs: Frequently Asked Questions
Which companies are hiring the most machine learning researchers?
The companies hiring the most machine learning researchers right now include Apple, Scale AI, and Achira, with the largest share of openings in California, Washington, and New York, based on current listings on Migrate Mate as of August 2026. Demand is concentrated at large technology companies, AI-focused startups, and research labs within healthcare and defense organizations.
How many machine learning research jobs are remote?
About 28% of machine learning research openings are fully remote or hybrid as of August 2026, reflecting the field's strong orientation toward asynchronous collaboration and distributed teams. Roles focused on natural language processing and data-centric research tend to be the most remote-friendly, while positions requiring access to specialized hardware or on-site lab infrastructure are more likely to require in-person presence.
How do you become a machine learning researcher?
Most machine learning researchers begin by earning a graduate degree in computer science, statistics, or a closely related field, where coursework covers optimization, probabilistic modeling, and neural network architectures. Building a public record of work through open-source contributions, competition placements, or preprints helps demonstrate capability. Applying to research internships at companies or labs while still in school is one of the most direct paths into a full-time research role.
Can you get a machine learning research job without a PhD?
Yes, candidates with a strong master's degree and a portfolio of published or well-documented independent research do get hired into machine learning research roles, particularly at applied research teams and AI product companies. What matters most is evidence of original thinking: a paper, a compelling open-source project, or a detailed write-up of a novel approach to a real problem. Roles labeled 'research engineer' or 'applied scientist' are often more accessible entry points than positions titled 'research scientist.'
What does the machine learning research interview process look like?
The process typically opens with a recruiter screen focused on background and research interests, followed by a technical phone screen covering machine learning concepts, coding in Python, and sometimes probability or statistics fundamentals. Onsite rounds usually include a research presentation of past work, one or two coding interviews, and a deep-dive conversation with senior researchers on your methods and trade-offs. Some companies also include a take-home research problem or a paper review discussion.
Where can I find and apply to machine learning research jobs?
You can find and apply to machine learning research jobs on Migrate Mate, which lists current openings from companies across the United States. Find roles that match your background and research focus, then apply directly to each listing. New positions are added regularly, so checking back often gives you a better chance of catching openings before they close.
See All 163+ Machine Learning Research Jobs
Find roles that match your experience and apply in just a few clicks.
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