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.
Find JobsOverview
Showing 5 of 444+ Machine Learning Research jobs
INTRODUCTION
It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive. As a global leader in robotic-assisted surgery and minimally invasive care, our technologies—like the da Vinci surgical system and Ion—have transformed how care is delivered for millions of patients worldwide.
We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.
The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful—because every improvement we make has the potential to change a life.
The Future Forward organization is Intuitive’s advanced concepts group. We explore emerging technologies, prototype next-generation solutions, and build software experiences that shape the future of robotic-assisted surgery.
If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare, you’ll find your purpose here.
ROLE AND RESPONSIBILITIES
Primary Function of Position
We are building advanced augmented dexterity capabilities for next-generation robotic platforms. As a Senior AI/ML Research Engineer (Computer Vision), you will develop the perception models that let our Embodied-AI system understand the surgical scene. Working within a hierarchical, multimodal stack—where a high-level model interprets sensory observations into structured intent and a low-level policy turns that intent into precise, safe, real-time control—you will focus on the vision layer: designing, training, and evaluating models that extract anatomy, instruments, actions, and surgical context from intraoperative video. You will partner with the broader AI/ML team to define how perception feeds reasoning and control, and you will drive the research-to-deployment path for your models, taking them from offline experimentation to robust, real-time performance in the OR.
Working within Intuitive's Future Forward research organization, you will identify, build and finetune the AI/ML models and algorithms that enables us to deliver safe and performant embodied AI systems. This role calls for someone who is equally comfortable getting hands-on with models and data and designing systems that scale.
- Develop temporal models for activity and workflow understanding: event/state recognition and fine-grained temporal action segmentation.
- Benchmark in-house models against the state of the art and recommend the target perception architecture.
- Define the perception input/output specification and demonstrate offline feasibility on recorded data.
- Stand up a continuous-improvement loop (discrepancy flagging, active learning, human-in-the-loop relabeling) and the tooling/UI needed for offline evaluation and the path to real-time use.
- Partner with annotation and data teams to shape label taxonomies, QC, and the data pipeline that feeds the AI/ML models.
- Establish the path from offline evaluation on recorded data to real-time integration, including the continuous-improvement (human-in-the-loop) data loop.
- Partner with AI/ML researchers, robotics, data engineers, and other stakeholders to deliver a perception layer that enables rapid prototyping and learning while working toward a product solution.
MINIMUM QUALIFICATIONS
- MS or PhD in CS, EE, Robotics, or a related field, with 5+ years of applied computer-vision research experience.
- Strong grasp of modern CV and deep-learning fundamentals: CNNs and vision transformers, segmentation, detection, tracking, and representation/self-supervised learning.
- Demonstrated work in video understanding, including temporal action segmentation, action/phase recognition, and video segmentation.
- Hands-on experience with modern video architectures, including video transformers and self-supervised video pretraining.
- Exposure to vision-action (VA) / vision-language-action (VLA) models and world-model / self-supervised predictive architectures (e.g., JEPA-style models, MAE, DINO) for learning visual representations and dynamics.
- Experience working with large, messy, real-world video datasets at scale.
- Strong software and experimentation skills in Python and C++, with proficiency in one or more of PyTorch/TensorFlow/JAX, and the ability to stand up clean, reproducible experiments and run the full loop (data curation, augmentation, loss design, metrics, error analysis).
- A research-and-prototyping mindset: comfortable working in ambiguity, framing open-ended problems, running rapid experiments, and reading and reproducing recent papers to pull promising techniques into practice.
- Sound judgment about the path from prototype to product: writing code others can build on, knowing when to optimize versus when to move fast, and thinking ahead about data quality, evaluation, and robustness even at the research stage.
- Solid foundations in linear algebra, probability, and optimization, enough to reason about and debug model behavior from first principles.
- Comfort collaborating across a multidisciplinary team (ML, robotics, software, and clinical/domain experts) and communicating tradeoffs and findings clearly.
PREFERRED QUALIFICATIONS
- Background in healthcare, medical devices, surgical robotics, or other regulated technical domains.
- Sim-to-real workflows and experience with robotics simulators (e.g., NVIDIA Isaac).
- Experience with structured, ontology- or taxonomy-based labeling frameworks for fine-grained activity.
- Multimodal fusion of video with sensor, telemetry, and system-log streams.
- Designing annotation pipelines, QC processes, and active-learning loops.
- Real-time / edge inference optimization (e.g., TensorRT, NVIDIA Jetson).
- Fine-grained interaction and object-relationship modeling.
- Relevant peer-reviewed publications (CVPR, ICCV, ECCV, NeurIPS, etc.).
ADDITIONAL INFORMATION
Due to the nature of our business and the role, please note that Intuitive and/or your customer(s) may require that you show current proof of vaccination against certain diseases including COVID-19. Details can vary by role.
Intuitive is an Equal Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type, without regard to race, sex, pregnancy, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws.
MANDATORY NOTICES
U.S. Export Controls Disclaimer: In accordance with the U.S. Export Administration Regulations (15 CFR §743.13(b)), some roles at Intuitive Surgical may be subject to U.S. export controls for prospective employees who are nationals from countries currently on embargo or sanctions status.
Certain information you provide as part of the application will be used for purposes of determining whether Intuitive Surgical will need to (i) obtain an export license from the U.S. Government on your behalf (note: the government’s licensing process can take 3 to 6+ months) or (ii) implement a Technology Control Plan (“TCP”) (note: typically adds 2 weeks to the hiring process).
For any Intuitive role subject to export controls, final offers are contingent upon obtaining an approved export license and/or an executed TCP prior to the prospective employee’s start date, which may or may not be flexible, and within a timeframe that does not unreasonably impede the hiring need. If applicable, candidates will be notified and instructed on any requirements for these purposes.
We will consider for employment qualified applicants with arrest and conviction records in accordance with fair chance laws.
Preference will be given to qualified candidates who do not reside, or plan to reside, in Alabama, Arkansas, Delaware, Florida, Indiana, Iowa, Louisiana, Maryland, Mississippi, Missouri, Oklahoma, Pennsylvania, South Carolina, or Tennessee.
This position may be filled at a different job level than listed here depending on business need and/or on the selected candidate’s experience, knowledge and skills.
Compensation will be based primarily on the job level at which the role is filled and the candidate’s qualifications, consistent with applicable law.
We provide market-competitive compensation packages, inclusive of base pay, incentives, benefits, and equity. It would not be typical for someone to be hired at the top end of range for the role, as actual pay will be determined based on several factors, including experience, skills, and qualifications. The target compensation ranges are listed.
Base Compensation Range Region 1: $196,800 USD - $283,200 USD
Base Compensation Range Region 2: $167,300 USD - $240,700 USD
Shift: Day
Workplace Type: Onsite - This job is fully onsite.
LOCATION
Sunnyvale, CA, United States
Not Remote
JOB TYPE
Engineering
JOB216052
INTRODUCTION
It started with a simple idea: what if surgery could be less invasive and recovery less painful? Nearly 30 years later, that question still fuels everything we do at Intuitive. As a global leader in robotic-assisted surgery and minimally invasive care, our technologies—like the da Vinci surgical system and Ion—have transformed how care is delivered for millions of patients worldwide.
We’re a team of engineers, clinicians, and innovators united by one purpose: to make surgery smarter, safer, and more human. Every day, our work helps care teams perform with greater precision and patients recover faster, improving outcomes around the world.
The problems we solve demand creativity, rigor, and collaboration. The work is challenging, but deeply meaningful—because every improvement we make has the potential to change a life.
The Future Forward organization is Intuitive’s advanced concepts group. We explore emerging technologies, prototype next-generation solutions, and build software experiences that shape the future of robotic-assisted surgery.
If you’re ready to contribute to something bigger than yourself and help transform the future of healthcare, you’ll find your purpose here.
ROLE AND RESPONSIBILITIES
Primary Function of Position
We are building advanced augmented dexterity capabilities for next-generation robotic platforms. As a Senior AI/ML Research Engineer (Computer Vision), you will develop the perception models that let our Embodied-AI system understand the surgical scene. Working within a hierarchical, multimodal stack—where a high-level model interprets sensory observations into structured intent and a low-level policy turns that intent into precise, safe, real-time control—you will focus on the vision layer: designing, training, and evaluating models that extract anatomy, instruments, actions, and surgical context from intraoperative video. You will partner with the broader AI/ML team to define how perception feeds reasoning and control, and you will drive the research-to-deployment path for your models, taking them from offline experimentation to robust, real-time performance in the OR.
Working within Intuitive's Future Forward research organization, you will identify, build and finetune the AI/ML models and algorithms that enables us to deliver safe and performant embodied AI systems. This role calls for someone who is equally comfortable getting hands-on with models and data and designing systems that scale.
- Develop temporal models for activity and workflow understanding: event/state recognition and fine-grained temporal action segmentation.
- Benchmark in-house models against the state of the art and recommend the target perception architecture.
- Define the perception input/output specification and demonstrate offline feasibility on recorded data.
- Stand up a continuous-improvement loop (discrepancy flagging, active learning, human-in-the-loop relabeling) and the tooling/UI needed for offline evaluation and the path to real-time use.
- Partner with annotation and data teams to shape label taxonomies, QC, and the data pipeline that feeds the AI/ML models.
- Establish the path from offline evaluation on recorded data to real-time integration, including the continuous-improvement (human-in-the-loop) data loop.
- Partner with AI/ML researchers, robotics, data engineers, and other stakeholders to deliver a perception layer that enables rapid prototyping and learning while working toward a product solution.
MINIMUM QUALIFICATIONS
- MS or PhD in CS, EE, Robotics, or a related field, with 5+ years of applied computer-vision research experience.
- Strong grasp of modern CV and deep-learning fundamentals: CNNs and vision transformers, segmentation, detection, tracking, and representation/self-supervised learning.
- Demonstrated work in video understanding, including temporal action segmentation, action/phase recognition, and video segmentation.
- Hands-on experience with modern video architectures, including video transformers and self-supervised video pretraining.
- Exposure to vision-action (VA) / vision-language-action (VLA) models and world-model / self-supervised predictive architectures (e.g., JEPA-style models, MAE, DINO) for learning visual representations and dynamics.
- Experience working with large, messy, real-world video datasets at scale.
- Strong software and experimentation skills in Python and C++, with proficiency in one or more of PyTorch/TensorFlow/JAX, and the ability to stand up clean, reproducible experiments and run the full loop (data curation, augmentation, loss design, metrics, error analysis).
- A research-and-prototyping mindset: comfortable working in ambiguity, framing open-ended problems, running rapid experiments, and reading and reproducing recent papers to pull promising techniques into practice.
- Sound judgment about the path from prototype to product: writing code others can build on, knowing when to optimize versus when to move fast, and thinking ahead about data quality, evaluation, and robustness even at the research stage.
- Solid foundations in linear algebra, probability, and optimization, enough to reason about and debug model behavior from first principles.
- Comfort collaborating across a multidisciplinary team (ML, robotics, software, and clinical/domain experts) and communicating tradeoffs and findings clearly.
PREFERRED QUALIFICATIONS
- Background in healthcare, medical devices, surgical robotics, or other regulated technical domains.
- Sim-to-real workflows and experience with robotics simulators (e.g., NVIDIA Isaac).
- Experience with structured, ontology- or taxonomy-based labeling frameworks for fine-grained activity.
- Multimodal fusion of video with sensor, telemetry, and system-log streams.
- Designing annotation pipelines, QC processes, and active-learning loops.
- Real-time / edge inference optimization (e.g., TensorRT, NVIDIA Jetson).
- Fine-grained interaction and object-relationship modeling.
- Relevant peer-reviewed publications (CVPR, ICCV, ECCV, NeurIPS, etc.).
ADDITIONAL INFORMATION
Due to the nature of our business and the role, please note that Intuitive and/or your customer(s) may require that you show current proof of vaccination against certain diseases including COVID-19. Details can vary by role.
Intuitive is an Equal Opportunity Employer. We provide equal employment opportunities to all qualified applicants and employees, and prohibit discrimination and harassment of any type, without regard to race, sex, pregnancy, sexual orientation, gender identity, national origin, color, age, religion, protected veteran or disability status, genetic information or any other status protected under federal, state, or local applicable laws.
MANDATORY NOTICES
U.S. Export Controls Disclaimer: In accordance with the U.S. Export Administration Regulations (15 CFR §743.13(b)), some roles at Intuitive Surgical may be subject to U.S. export controls for prospective employees who are nationals from countries currently on embargo or sanctions status.
Certain information you provide as part of the application will be used for purposes of determining whether Intuitive Surgical will need to (i) obtain an export license from the U.S. Government on your behalf (note: the government’s licensing process can take 3 to 6+ months) or (ii) implement a Technology Control Plan (“TCP”) (note: typically adds 2 weeks to the hiring process).
For any Intuitive role subject to export controls, final offers are contingent upon obtaining an approved export license and/or an executed TCP prior to the prospective employee’s start date, which may or may not be flexible, and within a timeframe that does not unreasonably impede the hiring need. If applicable, candidates will be notified and instructed on any requirements for these purposes.
We will consider for employment qualified applicants with arrest and conviction records in accordance with fair chance laws.
Preference will be given to qualified candidates who do not reside, or plan to reside, in Alabama, Arkansas, Delaware, Florida, Indiana, Iowa, Louisiana, Maryland, Mississippi, Missouri, Oklahoma, Pennsylvania, South Carolina, or Tennessee.
This position may be filled at a different job level than listed here depending on business need and/or on the selected candidate’s experience, knowledge and skills.
Compensation will be based primarily on the job level at which the role is filled and the candidate’s qualifications, consistent with applicable law.
We provide market-competitive compensation packages, inclusive of base pay, incentives, benefits, and equity. It would not be typical for someone to be hired at the top end of range for the role, as actual pay will be determined based on several factors, including experience, skills, and qualifications. The target compensation ranges are listed.
Base Compensation Range Region 1: $196,800 USD - $283,200 USD
Base Compensation Range Region 2: $167,300 USD - $240,700 USD
Shift: Day
Workplace Type: Onsite - This job is fully onsite.
LOCATION
Sunnyvale, CA, United States
Not Remote
JOB TYPE
Engineering
JOB216052
See All 444+ Machine Learning Research Jobs
Jump back to the full list of openings and apply to any machine learning research role that fits.
Find JobsMachine Learning Research Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Apple49
- Scale AI41
- Microsoft21
- TikTok21
- Meta19
Top Industries Hiring
- Technology & Software180
- Artificial Intelligence78
- Electronics & Hardware77
- Science & Research34
- Banking & Financial Services26
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 Microsoft, with the largest share of openings in California, Washington, and New York, based on current listings on Migrate Mate as of June 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 14% of machine learning research openings are fully remote or hybrid as of June 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 444+ Machine Learning Research Jobs
Jump back to the full list of openings and apply to any machine learning research role that fits.
Find Jobs