AI Trainer Jobs
AI Trainer jobs are open across technology, edtech, and enterprise software companies, from entry-level annotation roles to senior curriculum design and model evaluation positions, with specializations in RLHF, prompt engineering, and conversational AI. Scan the live roles below and apply to whichever ones fit.
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Posting Details
The successful candidate will teach graduate-level courses in Artificial Intelligence and Machine Learning, with a particular emphasis on applications in Biomedical Sciences, Environmental Science, and Environmental Public Health, as well as undergraduate courses as needed.
We seek an enthusiastic, innovative, and student-centered educator who is passionate about advancing AI education, mentoring students, and applying emerging technologies to real-world scientific and public health challenges.
The selected candidate will have the opportunity to contribute to the University’s new interdisciplinary Master’s program in Artificial Intelligence and Machine Learning for Biomedical and Environmental Health Systems (AIM-BEHS), helping prepare the next generation of professionals to use AI-driven approaches to address critical challenges in healthcare, biomedical research, environmental sustainability, and public health.
- A Ph.D. in Artificial Intelligence, Machine Learning, Data Science, Computer Science, Computational Science, Biomedical Sciences, Environmental Science, Environmental Health, Environmental Public Health, Engineering, or a closely related field by the start date of appointment.
- Demonstrated expertise or a strong academic or research background in AI, Machine Learning, Data Science, or computational methods, with the ability to apply these technologies to biomedical, environmental, or public health challenges.
- Demonstrated ability or strong potential to teach graduate-level courses in Artificial Intelligence, Machine Learning, and related disciplines, including interdisciplinary applications.
- Evidence of scholarly achievement, research experience, or strong potential to develop research projects and engage graduate and undergraduate students in research and applied learning.
- Ability and willingness to collaborate with faculty and researchers from diverse scientific and technical disciplines.
- Strong communication, organizational, and interpersonal skills, with a commitment to effective teaching, student mentorship, and academic excellence.
- Commitment to supporting student success, interdisciplinary education, scholarly activities, and university service.
- Teaching, research, postdoctoral, or relevant industry experience in Artificial Intelligence, Machine Learning, or Data Science.
- Experience with AI/ML tools and programming environments such as Python, R, TensorFlow, PyTorch, or related technologies.
- Experience applying AI/ML techniques to biomedical research, Bioinformatics, healthcare, environmental monitoring, environmental health, or public health data.
- Experience developing interdisciplinary research projects, mentoring students, or collaborating on externally funded research.
- Familiarity with emerging AI technologies, including deep learning, generative AI, and advanced data analytics.
- Interest in contributing to the development and growth of a new interdisciplinary graduate program.
- Curriculum vitae.
- One combined document that includes:
- Cover letter describing teaching and research interests.
- Statement of teaching philosophy.
- Statement of research interests, including plans for student involvement.
- All graduate transcripts (unofficial transcripts are acceptable for initial review).
- Names and contact information for three professional references.
- Three professional reference letters.
Equal Opportunity Statement
Supplemental Questions
Required fields are indicated with an asterisk (*).
Documents Needed To Apply
- Resume
- Cover Letter
- Transcripts
- Letter of Recommendation
- Curriculum Vitae
- Portfolio
Posting Details
The successful candidate will teach graduate-level courses in Artificial Intelligence and Machine Learning, with a particular emphasis on applications in Biomedical Sciences, Environmental Science, and Environmental Public Health, as well as undergraduate courses as needed.
We seek an enthusiastic, innovative, and student-centered educator who is passionate about advancing AI education, mentoring students, and applying emerging technologies to real-world scientific and public health challenges.
The selected candidate will have the opportunity to contribute to the University’s new interdisciplinary Master’s program in Artificial Intelligence and Machine Learning for Biomedical and Environmental Health Systems (AIM-BEHS), helping prepare the next generation of professionals to use AI-driven approaches to address critical challenges in healthcare, biomedical research, environmental sustainability, and public health.
- A Ph.D. in Artificial Intelligence, Machine Learning, Data Science, Computer Science, Computational Science, Biomedical Sciences, Environmental Science, Environmental Health, Environmental Public Health, Engineering, or a closely related field by the start date of appointment.
- Demonstrated expertise or a strong academic or research background in AI, Machine Learning, Data Science, or computational methods, with the ability to apply these technologies to biomedical, environmental, or public health challenges.
- Demonstrated ability or strong potential to teach graduate-level courses in Artificial Intelligence, Machine Learning, and related disciplines, including interdisciplinary applications.
- Evidence of scholarly achievement, research experience, or strong potential to develop research projects and engage graduate and undergraduate students in research and applied learning.
- Ability and willingness to collaborate with faculty and researchers from diverse scientific and technical disciplines.
- Strong communication, organizational, and interpersonal skills, with a commitment to effective teaching, student mentorship, and academic excellence.
- Commitment to supporting student success, interdisciplinary education, scholarly activities, and university service.
- Teaching, research, postdoctoral, or relevant industry experience in Artificial Intelligence, Machine Learning, or Data Science.
- Experience with AI/ML tools and programming environments such as Python, R, TensorFlow, PyTorch, or related technologies.
- Experience applying AI/ML techniques to biomedical research, Bioinformatics, healthcare, environmental monitoring, environmental health, or public health data.
- Experience developing interdisciplinary research projects, mentoring students, or collaborating on externally funded research.
- Familiarity with emerging AI technologies, including deep learning, generative AI, and advanced data analytics.
- Interest in contributing to the development and growth of a new interdisciplinary graduate program.
- Curriculum vitae.
- One combined document that includes:
- Cover letter describing teaching and research interests.
- Statement of teaching philosophy.
- Statement of research interests, including plans for student involvement.
- All graduate transcripts (unofficial transcripts are acceptable for initial review).
- Names and contact information for three professional references.
- Three professional reference letters.
Equal Opportunity Statement
Supplemental Questions
Required fields are indicated with an asterisk (*).
Documents Needed To Apply
- Resume
- Cover Letter
- Transcripts
- Letter of Recommendation
- Curriculum Vitae
- Portfolio
See All 486+ AI Trainer Jobs
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Find AI Trainer JobsAI Trainer Job Market
Who's Hiring
- Meridial167
- Booz Allen Hamilton12
- JPMorganChase10
- DataAnnotation9
- Johns Hopkins University Applied Physics Laboratory9
Top Industries Hiring
- Banking & Financial Services10
- Education8
- Technology & Software8
- Healthcare & Medical Services5
- Investment & Asset Management3
What Employers Look For
The qualifications that appear most often in AI trainer jobs.
- Experience writing, ranking, or evaluating prompts and AI-generated outputs
- Strong written English skills with attention to grammar, tone, and factual accuracy
- Familiarity with RLHF, instruction tuning, or supervised fine-tuning workflows
- Background in a specific domain such as coding, medicine, law, or STEM fields
- Ability to follow detailed annotation guidelines and maintain high inter-rater agreement
- Bachelor's degree or equivalent experience in a relevant technical or humanities discipline
Tips for Your AI Trainer Job Search
Tailor your resume to task types
AI trainer roles split between annotation, evaluation, and instruction design. Call out which task types you have done, such as ranking model outputs, writing prompts, or labeling datasets, so hiring managers can place you immediately without guessing.
Show domain expertise on your resume
Many ai trainer postings target specific verticals like legal, medical, or coding. If your background fits one of those areas, lead with it. A general trainer resume loses to a candidate who signals domain depth from the first line.
Apply early to roles that fit
Migrate Mate lists ai trainer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter postings by annotation platform experience
Job descriptions often list specific labeling or evaluation platforms as requirements. Search for openings that name platforms you already know, since platform familiarity shortens onboarding and strengthens your application against candidates who need training.
Prepare a prompt or evaluation sample
Many ai trainer interviews include a live task where you write prompts, rank outputs, or flag errors in generated text. Practicing on a few examples before your interview makes the difference between a confident performance and a fumbled one.
Negotiate scope, not just pay
AI trainer contracts and full-time roles vary widely in task type, model access, and autonomy. Before accepting, clarify which models you will work on, whether the work shifts over time, and how feedback you give gets used, so you are not locked into repetitive low-complexity tasks.
AI Trainer Jobs: Frequently Asked Questions
Which companies are hiring the most ai trainers?
The most active employers for ai trainers right now are Meridial, Booz Allen Hamilton, and JPMorganChase, and the most openings are in Texas, California, and Virginia, based on current listings on Migrate Mate as of November 2026. Demand is especially concentrated at AI labs, enterprise software companies, and vendors that supply human feedback data to foundation model teams.
How many ai trainer jobs are remote?
About 80% of ai trainer openings are fully remote or hybrid as of November 2026, making it one of the more flexible roles in the technology sector. Annotation, prompt writing, and output evaluation tasks tend to be the most remote-friendly, while roles that involve live model testing or team instruction design more often require some in-office presence.
How do you become a ai trainer?
Start by building familiarity with how large language models generate text and where they fail, since evaluation work requires spotting subtle errors in fluency, reasoning, and factual accuracy. Take on freelance annotation or evaluation projects to build a task history, document the guidelines you followed, and collect examples of your output. Then apply to roles that match the domain where your background is strongest.
How do you get hired as a ai trainer with little or no experience?
Focus on roles that list strong writing ability and domain knowledge as the core requirements rather than platform experience, since those skills transfer directly. Write a few sample prompts or model evaluations to show during interviews, and highlight any work that required close reading, fact-checking, or structured feedback, such as editing, tutoring, research, or technical writing. Entry-level annotation contracts are a common first step into full-time trainer roles.
What does the ai trainer interview process look like?
Most ai trainer interviews include a screening call focused on your writing background and domain expertise, followed by a skills task where you write prompts, evaluate model outputs, or flag errors in generated text using a provided rubric. Some employers add a second round with a team lead to discuss your reasoning on the task. The process moves faster than typical engineering hiring, often concluding within two to three weeks.
Where can I find and apply to ai trainer jobs?
You can find and apply to ai trainer jobs on Migrate Mate, which lists current openings from across the United States. Search the roles available, find the ones that match your background and target domain, and apply directly to each listing that fits.
See All 486+ AI Trainer Jobs
Find roles that match your experience and apply in just a few clicks.
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