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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Showing 5 of 148+ ML Research Engineer 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:
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
- Apple25
- Scale AI23
- Achira5A
- Nuro4
- Exponent4
Top Industries Hiring
- Technology & Software28
- Artificial Intelligence26
- Electronics & Hardware17
- Banking & Financial Services7
- Investment & Asset Management7
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 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 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 31% of ml research engineer openings are fully remote or hybrid as of August 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 148+ ML Research Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find ML Research Engineer Jobs