AI/ML Researcher Jobs
AI/ML Researcher jobs are open from new-grad to principal level across technology, healthcare, finance, and defense, with common specializations in natural language processing, computer vision, and reinforcement learning. See the openings below and apply to the ones that match your experience.
Find AI/ML Researcher JobsLooking for remote work? View remote AI/ML researcher jobs →Overview
Showing 5 of 1,000+ AI/ML Researcher jobs
INTRODUCTION
NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. We are looking for outstanding ML/DL compiler engineers to join the team and develop groundbreaking technologies in machine learning compilers and AI systems. We build innovative AI compiler solutions that work together with NVIDIA's software stack to provide comprehensive acceleration for modern machine learning models. As a member of the team, you will develop innovative AI compiler technologies for NVIDIA's hardware architecture. You will develop new ML/DL compiler abstractions, build efficient attention runtimes, and ML/DL-compiler driven system solutions to accelerate large language models, agents, and other high-impact machine learning workloads. As part of this role, you will be building a close technical relationship with internal NVIDIA software and hardware teams to push the latest developments to NVIDIA's product.
ROLE AND RESPONSIBILITIES
What You’ll Be Doing
- Innovate and develop new machine learning compiler and systems technologies
- Design, implement, and optimize compilers for high impact AI workloads
- Building strong kernel and domain specific language solutions for state of art kernels in LLM inference workloads
- Developing AI-driven solutions to automate the overall development flow
- Co-design learning system solutions with current and future ML compiler and algorithm technologies
- Collaborate closely with other engineering teams at NVIDIA to build high impact solutions for machine learning acceleration
BASIC QUALIFICATIONS
What We Need To See
- Bachelor's degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); MS or PhD are preferred
- 6+ years (academic/industry) experience in machine learning systems development – including ML compilers, LLM inference kernels, kernel generations
- Strong experience in developing or using deep learning frameworks (e.g. PyTorch, JAX etc)
- Strong python and C/C++ programming skills
PREFERRED QUALIFICATIONS
Ways To Stand Out From The Crowd
- Expertise in AI frameworks such as PyTorch, TensorFlow, and ONNX
- Expertise in machine learning compilers (e.g. Apache TVM, MLIR)
- Expertise in domain specific compiler and library solutions for LLM inference and training (e.g. FlashInfer, Flash Attention)
- Strong experience in GPU performance optimizations as well as experience machine learning systems research and productization
- Open source project ownership or contributions
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 29, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
JR2019867
INTRODUCTION
NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. We are looking for outstanding ML/DL compiler engineers to join the team and develop groundbreaking technologies in machine learning compilers and AI systems. We build innovative AI compiler solutions that work together with NVIDIA's software stack to provide comprehensive acceleration for modern machine learning models. As a member of the team, you will develop innovative AI compiler technologies for NVIDIA's hardware architecture. You will develop new ML/DL compiler abstractions, build efficient attention runtimes, and ML/DL-compiler driven system solutions to accelerate large language models, agents, and other high-impact machine learning workloads. As part of this role, you will be building a close technical relationship with internal NVIDIA software and hardware teams to push the latest developments to NVIDIA's product.
ROLE AND RESPONSIBILITIES
What You’ll Be Doing
- Innovate and develop new machine learning compiler and systems technologies
- Design, implement, and optimize compilers for high impact AI workloads
- Building strong kernel and domain specific language solutions for state of art kernels in LLM inference workloads
- Developing AI-driven solutions to automate the overall development flow
- Co-design learning system solutions with current and future ML compiler and algorithm technologies
- Collaborate closely with other engineering teams at NVIDIA to build high impact solutions for machine learning acceleration
BASIC QUALIFICATIONS
What We Need To See
- Bachelor's degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); MS or PhD are preferred
- 6+ years (academic/industry) experience in machine learning systems development – including ML compilers, LLM inference kernels, kernel generations
- Strong experience in developing or using deep learning frameworks (e.g. PyTorch, JAX etc)
- Strong python and C/C++ programming skills
PREFERRED QUALIFICATIONS
Ways To Stand Out From The Crowd
- Expertise in AI frameworks such as PyTorch, TensorFlow, and ONNX
- Expertise in machine learning compilers (e.g. Apache TVM, MLIR)
- Expertise in domain specific compiler and library solutions for LLM inference and training (e.g. FlashInfer, Flash Attention)
- Strong experience in GPU performance optimizations as well as experience machine learning systems research and productization
- Open source project ownership or contributions
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 29, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
JR2019867
Top Cities Hiring AI/ML Researchers
Explore AI/ML researcher openings in the cities hiring most right now.
See All 1,000+ AI/ML Researcher Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI/ML Researcher JobsAI/ML Researcher Job Market
Who's Hiring
- Apple61
- Capital One30
- Booz Allen Hamilton29
- Google21
- TikTok21
Top Industries Hiring
- Technology & Software294
- Consulting & Professional Services83
- Electronics & Hardware81
- Banking & Financial Services79
- Retail50
What Employers Look For
The qualifications that appear most often in AI/ML researcher jobs.
- PhD or Master's degree 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 experiments with large-scale datasets
- Familiarity with transformer architectures and modern foundation model techniques
- Published research or demonstrated contributions to the machine learning community
- Ability to communicate technical findings clearly to cross-functional stakeholders
Tips for Your AI/ML Researcher Job Search
Tailor your resume to the method
Hiring managers scan for the specific modeling approaches you've used, not just 'machine learning.' Name the algorithms, architectures, and frameworks you applied and pair each with a concrete outcome, such as a reduction in error rate or an improvement in inference speed.
Link every project to a public artifact
Reviewers for research roles expect to verify your work. Attach a preprint, a conference paper, a public repository, or a technical blog post to each major project on your resume so they can read beyond the bullet point.
Apply early to roles that fit
Migrate Mate lists ai/ml researcher 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 overlap heavily in this field. Read the responsibilities section carefully to distinguish pure research roles, which expect publications and novel contributions, from applied science roles, which weight production deployment and cross-functional delivery. Applying to the wrong type wastes your time.
Prepare a paper walkthrough for interviews
Many ai/ml researcher interviews include a research presentation or a deep dive into a paper you authored or admire. Practice explaining your methodological choices, the limitations of your approach, and what you would do differently, not just the results.
Negotiate compute and data access, not just pay
Research velocity depends on GPU budgets, proprietary datasets, and cloud credits. Ask specifically about compute allocation policies, internal dataset access, and whether the team has a publication approval process before accepting any offer.
AI/ML Researcher Jobs: Frequently Asked Questions
Which companies are hiring the most ai/ml researchers?
The companies hiring the most ai/ml researchers right now include Apple, Capital One, and Booz Allen Hamilton, with the largest share of openings in California, Virginia, and Washington, based on current listings on Migrate Mate as of June 2026. Demand is concentrated in technology, cloud infrastructure, and enterprise software companies investing in generative AI and foundation model development.
How many ai/ml researcher jobs are remote?
About 36% of ai/ml researcher openings are fully remote or hybrid as of June 2026, making it one of the more flexible research disciplines in terms of location. Roles focused on natural language processing and data-centric research tend to offer the highest share of fully remote options, while hardware-adjacent or lab-based positions more often require on-site presence.
How do you become an ai/ml researcher?
Most ai/ml researchers build a foundation through a graduate degree in computer science, mathematics, or a closely related field, then develop applied skills through thesis research, internships, or open-source contributions. Publishing or presenting at recognized machine learning venues strengthens your candidacy significantly. Building a public portfolio of reproducible experiments and contributing to collaborative research projects rounds out the profile employers look for.
Can you get an ai/ml researcher job with little or no experience?
Breaking in with limited experience is possible but requires a deliberate portfolio strategy. Focus on completing end-to-end projects that involve a clearly stated problem, a novel or well-justified methodological choice, and a reproducible result. Contributing to open-source research codebases, co-authoring papers with academics, or completing a research internship at a company or national lab are the most direct paths employers recognize when your formal experience is thin.
What does the ai/ml researcher interview process look like?
The process typically opens with a recruiter screen followed by a technical phone interview covering machine learning fundamentals, probability, and coding. A research presentation or paper deep-dive is common at the next stage, where you walk through your own work or a selected paper and field detailed methodological questions. Final rounds usually include a full-day set of interviews covering research vision, system design for ML pipelines, and cross-functional collaboration scenarios.
Where can I find and apply to ai/ml researcher jobs?
You can find and apply to ai/ml researcher 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 background and apply directly to each one that fits.
See All 1,000+ AI/ML Researcher Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI/ML Researcher Jobs