AI Research Engineer Jobs
AI Research Engineer jobs are open across technology, healthcare, finance, and defense, at every level from new-grad to principal and staff, with specializations in machine learning, natural language processing, and computer vision. Find a role that fits from the openings below and apply directly.
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Overview
The Generative AI Research Engineer Intern conducts primary and secondary research of advanced and emerging healthcare informatics technology with a focus on Generative AI and emerging Artificial General Intelligence technology for healthcare treatment, payment, and operations use cases. Creates research papers, analytical reports, proposals, and educational material. Maintains a deep understanding of technology trends and hands-on experience with relevant technologies. Develops generative AI models, architectures, databases, and systems to improve healthcare solutions. We are currently looking for interns who can start in the Summer or Fall of 2026.
Responsibilities
NOTE: There are multiple open intern positions. Hours and length of assignment will be at the intern's choice from 20 - 40 hours per week with a minimum of one semester up to one year.
Technical Expertise
- Demonstrates a strong understanding of technology trends, research, and emerging technologies relevant to the healthcare industry, particularly in Generative AI.
- Assists in developing and improving LLMs and ML tools used across the organization.
- Assists in establishing and maintaining an Artificial Intelligence Governance Program.
Communication & Collaboration
- Communicates technology-related updates and requirements to other departments and contributes to presentations for senior management.
- Collaborates with research and development teams, product management, and strategic analysts to support ongoing projects.
Leadership & Management
- Partners with Business Units to provide reliable intelligence, validated technology options, and insights on enterprise and industry trends.
- Supports technology project teams by coordinating specific tasks, assisting with day-to-day operations, and contributing to the successful delivery of solutions.
- Assists in collaborative efforts with academic research teams, practicums, internships, and vendor POCs.
External Relationships & Partnerships
- Supports vendor evaluations and contributes to collaborations with vendors.
- Assists as a liaison between academic institutions, professional organizations, and research groups as needed.
Other
- Support the Academic Corporate Engagement efforts to develop research and educational talent, with a focus on enhancing health tech knowledge and skills.
- Complete all responsibilities and goals outlined in the internship program.
- Complete all special projects and other duties as assigned.
- Must be able to perform duties with or without reasonable accommodation.
This job description is intended to describe the general nature and level of work being performed in this internship. It is not an exhaustive list of responsibilities, duties, and skills required and does not constitute an employment agreement. This job description is subject to change as Cotiviti’s needs and requirements of the internship evolve.
QUALIFICATIONS
- Currently pursuing or recently completed an advanced degree in healthcare, technology, or a related field (e.g., Biomedical Informatics, Computer Science) with preference of a PhD.
- Demonstrated interest or experience in AI, healthcare technology, or informatics research.
- Strong foundational knowledge in generative AI model development, architectures, and vector databases.
- Hands-on experience with working with Machine Learning and Deep Learning models. Experience with LLM/RAG models and LLM fine-tuning is a plus.
- Hands-on experience working with cloud services (AWS/Azure), large data sets, and building data pipelines for ML solutions. Experience with vector embeddings and databases is a plus.
- Ability to work collaboratively and communicate effectively with cross-functional teams.
MENTAL REQUIREMENTS
- Communicating with others to exchange information.
- Assessing the accuracy, neatness, and thoroughness of the work assigned.
PHYSICAL REQUIREMENTS AND WORKING CONDITIONS
- Remaining in a stationary position, often standing or sitting for prolonged periods.
- Repeating motions that may include the wrists, hands, and/or fingers.
- Must be able to provide a dedicated, secure work area.
- Must be able to provide high-speed internet access/connectivity and office setup and maintenance.
- No adverse environmental conditions are expected.
COMPENSATION
- Base compensation ranges from $32.00 to $40.00 per hour. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs.
Nonexempt employees are eligible to receive overtime pay for hours worked in excess of 40 hours in a given week, or as otherwise required by applicable state law.
Date of posting: 6/1/2026
Applications are assessed on a rolling basis. We anticipate that the application window will close on 8/21/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected.
Overview
The Generative AI Research Engineer Intern conducts primary and secondary research of advanced and emerging healthcare informatics technology with a focus on Generative AI and emerging Artificial General Intelligence technology for healthcare treatment, payment, and operations use cases. Creates research papers, analytical reports, proposals, and educational material. Maintains a deep understanding of technology trends and hands-on experience with relevant technologies. Develops generative AI models, architectures, databases, and systems to improve healthcare solutions. We are currently looking for interns who can start in the Summer or Fall of 2026.
Responsibilities
NOTE: There are multiple open intern positions. Hours and length of assignment will be at the intern's choice from 20 - 40 hours per week with a minimum of one semester up to one year.
Technical Expertise
- Demonstrates a strong understanding of technology trends, research, and emerging technologies relevant to the healthcare industry, particularly in Generative AI.
- Assists in developing and improving LLMs and ML tools used across the organization.
- Assists in establishing and maintaining an Artificial Intelligence Governance Program.
Communication & Collaboration
- Communicates technology-related updates and requirements to other departments and contributes to presentations for senior management.
- Collaborates with research and development teams, product management, and strategic analysts to support ongoing projects.
Leadership & Management
- Partners with Business Units to provide reliable intelligence, validated technology options, and insights on enterprise and industry trends.
- Supports technology project teams by coordinating specific tasks, assisting with day-to-day operations, and contributing to the successful delivery of solutions.
- Assists in collaborative efforts with academic research teams, practicums, internships, and vendor POCs.
External Relationships & Partnerships
- Supports vendor evaluations and contributes to collaborations with vendors.
- Assists as a liaison between academic institutions, professional organizations, and research groups as needed.
Other
- Support the Academic Corporate Engagement efforts to develop research and educational talent, with a focus on enhancing health tech knowledge and skills.
- Complete all responsibilities and goals outlined in the internship program.
- Complete all special projects and other duties as assigned.
- Must be able to perform duties with or without reasonable accommodation.
This job description is intended to describe the general nature and level of work being performed in this internship. It is not an exhaustive list of responsibilities, duties, and skills required and does not constitute an employment agreement. This job description is subject to change as Cotiviti’s needs and requirements of the internship evolve.
QUALIFICATIONS
- Currently pursuing or recently completed an advanced degree in healthcare, technology, or a related field (e.g., Biomedical Informatics, Computer Science) with preference of a PhD.
- Demonstrated interest or experience in AI, healthcare technology, or informatics research.
- Strong foundational knowledge in generative AI model development, architectures, and vector databases.
- Hands-on experience with working with Machine Learning and Deep Learning models. Experience with LLM/RAG models and LLM fine-tuning is a plus.
- Hands-on experience working with cloud services (AWS/Azure), large data sets, and building data pipelines for ML solutions. Experience with vector embeddings and databases is a plus.
- Ability to work collaboratively and communicate effectively with cross-functional teams.
MENTAL REQUIREMENTS
- Communicating with others to exchange information.
- Assessing the accuracy, neatness, and thoroughness of the work assigned.
PHYSICAL REQUIREMENTS AND WORKING CONDITIONS
- Remaining in a stationary position, often standing or sitting for prolonged periods.
- Repeating motions that may include the wrists, hands, and/or fingers.
- Must be able to provide a dedicated, secure work area.
- Must be able to provide high-speed internet access/connectivity and office setup and maintenance.
- No adverse environmental conditions are expected.
COMPENSATION
- Base compensation ranges from $32.00 to $40.00 per hour. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs.
Nonexempt employees are eligible to receive overtime pay for hours worked in excess of 40 hours in a given week, or as otherwise required by applicable state law.
Date of posting: 6/1/2026
Applications are assessed on a rolling basis. We anticipate that the application window will close on 8/21/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected.
See All 712+ AI Research Engineer Jobs
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Find AI Research Engineer JobsAI Research Engineer Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Apple53
- Scale AI46
- Meta40
- Microsoft34
- ByteDance32
Top Industries Hiring
- Technology & Software318
- Artificial Intelligence104
- Science & Research83
- Electronics & Hardware82
- Education55
What Employers Look For
The qualifications that appear most often in AI research engineer jobs.
- Master's or PhD in computer science, machine learning, or a related quantitative field
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience designing, training, and evaluating large-scale machine learning models
- Familiarity with distributed training systems and GPU cluster environments
- Strong mathematical foundation in linear algebra, probability, and optimization
- Demonstrated research output such as publications, preprints, or open-source contributions
Tips for Your AI Research Engineer Job Search
Tailor your resume to model types
Hiring managers scan for the specific model architectures you've worked with, not just 'machine learning experience.' Name the frameworks, model families, and scale of training runs on your resume so reviewers can immediately match your background to their stack.
Build a public research artifact
A preprint, a well-documented GitHub repo, or a reproducible benchmark result carries more weight than coursework for AI research roles. Link to something you built or contributed to so hiring teams can evaluate your thinking before the first screen.
Apply early to roles that fit
Migrate Mate lists ai 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 scope before applying
Some ai research engineer roles are fundamental research positions, others are applied or product-focused. Read job descriptions for phrases like 'publish at top venues' versus 'deploy to production' so you target openings that match the work you actually want to do.
Prepare a paper walkthrough for interviews
Most ai research engineer loops include a deep-dive on a paper you've authored or studied closely. Practice explaining the motivation, methodology, and limitations out loud, including what you'd do differently, because interviewers probe well beyond surface-level summaries.
Negotiate compute access alongside compensation
For research roles, GPU budget and cluster access directly affect what you can accomplish. Ask early in the offer stage about available compute resources, research cycles separate from product work, and publication policy so you understand the real conditions of the job.
AI Research Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most ai research engineers?
The companies hiring the most ai research engineers right now include Apple, Scale AI, and Meta, with the largest share of openings in California, Washington, and New York, based on current listings on Migrate Mate as of June 2026. Openings are concentrated at technology companies, defense contractors, and healthcare AI teams building and scaling foundation models.
How many ai research engineer jobs are remote?
About 16% of ai research engineer openings are fully remote or hybrid as of June 2026, making it one of the more remote-accessible engineering specializations. Roles focused on modeling, evaluation, and literature research tend to be the most remote-friendly, while positions involving on-site compute infrastructure or hardware-adjacent research more often require in-person presence.
How do you become an ai research engineer?
Most ai research engineers start with a strong foundation in mathematics and computer science, then deepen expertise through graduate coursework or independent study in machine learning. Building hands-on projects, contributing to open-source models, and producing public research artifacts like preprints or reproducible benchmarks are the steps that move a candidate from eligible to competitive in most hiring processes.
How do you get hired as an ai research engineer with little experience?
Candidates with limited industry experience get traction by publishing or posting reproducible work in a specific subfield, such as fine-tuning language models or benchmarking vision systems, rather than trying to appear broadly qualified. Targeting applied research roles at mid-size companies, contributing to well-known open-source projects, and entering through a research internship or contractor position are the most common entry paths.
What does the ai research engineer interview process look like?
Most ai research engineer interview loops include a recruiter screen, a technical coding round covering algorithms and data structures, a machine learning fundamentals discussion, and a research deep-dive where you walk through a paper you know well or a project you built. Some companies add a system design round focused on ML infrastructure and a final panel with research leads who evaluate scientific thinking and communication.
Where can I find and apply to ai research engineer jobs?
You can find and apply to ai research engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your background and the type of research you want to do, then apply directly to each one that fits.
See All 712+ AI Research Engineer Jobs
Jump back to the full list of openings and apply to any AI research engineer role that fits.
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