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Generative Ai Instructor Jobs in Carlisle, MA (NOW HIRING)

Axis

AI Enablement Specialist

Chelmsford, MA · On-site

$100/hr

Understanding of generative AI mechanics, including prompt engineering and the ethical implications ... Trainer / instructor experience a pro Physical Demands and Travel: Reasonable accommodations may be ...

All JobsGenerative Ai Instructor JobsGenerative Ai Instructor Jobs in Carlisle, MA

Generative Ai Instructor information

What does a generative AI instructor do?

A Generative AI Instructor is responsible for teaching individuals or groups about generative artificial intelligence technologies, such as machine learning models that create new content (text, images, audio, etc.). They design curriculum, lead workshops, and provide hands-on demonstrations to help students understand how to build, fine-tune, and deploy generative AI models. Additionally, they stay updated on the latest advancements in AI and help learners understand ethical considerations and real-world applications of generative AI.

What are some common challenges generative AI instructors face when teaching complex concepts to diverse learners?

Generative AI Instructors often encounter the challenge of breaking down advanced machine learning and artificial intelligence concepts into digestible lessons for students with varying backgrounds. Balancing the technical depth required for industry relevance with accessibility for beginners requires flexible teaching strategies and strong communication skills. Additionally, keeping course materials up-to-date with the rapidly evolving AI landscape is essential, which means instructors must continually learn and adapt their curriculum. Collaboration with peers and industry professionals is common to ensure content accuracy and relevance.

What are the key skills and qualifications needed to thrive as a generative AI instructor, and why are they important?

To thrive as a Generative AI Instructor, you need a deep understanding of machine learning, natural language processing, and AI concepts, often supported by a degree in computer science or a related field. Familiarity with tools like Python, TensorFlow, PyTorch, and platforms such as Jupyter Notebook is typically required, along with experience using generative AI frameworks and models. Strong communication, adaptability, and the ability to simplify complex topics for diverse learners are important soft skills in this role. These skills ensure effective teaching, empower students to grasp advanced AI concepts, and keep coursework relevant in a fast-evolving field.

What is the difference between Generative Ai Instructor vs Data Scientist?

AspectGenerative Ai InstructorData Scientist
Required CredentialsAI/ML certifications, teaching experienceStatistics, programming, data analysis degrees
Work EnvironmentEducational settings, online platformsResearch labs, tech companies, finance
Employer & Industry UsageEdTech, training programsTech firms, finance, healthcare

While both roles involve AI expertise, a Generative Ai Instructor primarily focuses on teaching and training others in generative AI techniques, often within educational or training environments. In contrast, a Data Scientist analyzes data to derive insights and build models across various industries. Both roles require strong technical skills, but their core responsibilities and work settings differ significantly.

Generative Ai Instructor jobs near you
Infographic showing various Generative Ai Instructor job openings in Carlisle, MA as of August 2026, with employment types broken down into 75% Full Time, 21% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution.

Adjunct Instructor in Generative AI and Large Language Models in Analytics

Brandeis University

Waltham, MA • On-site

$6.5K/mo

Part-time

Re-posted 17 days ago

Job description

Brandeis University's Online Applied Data Science and Decision Analytics Program is seeking an Adjunct Faculty member for RADS 140 Generative AI and Large Language Models in Analytics for the Fall-2 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Applied Data Science and Decision Analytics.
This course will examine the design, implementation, and governance of generative AI systems particularly Large Language Models (LLMs) for analytics and decision-support applications. Students explore prompt engineering, fine-tuning, evaluation metrics, hallucination mitigation, and responsible deployment practices.
Core Course Responsibilities Summary
  • Course Logistics and Facilitation: Focuses on the organized and timely rollout of course content, maintaining consistent communication through weekly announcements, and ensuring all instructional activities occur within university-approved digital platforms.
  • Instructor Presence and Engagement: Centers on building an active teaching persona by hosting live introductory sessions, facilitating weekly academic discourse in forums, and maintaining regular availability for student consultation.
  • Individual Feedback and Grading: Emphasizes the professional obligation to provide transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe.
  • Professional Conduct and Standards: Requires adherence to university communication protocols, the promotion of respectful online "netiquette," and ensuring the course meets accessibility and technical visibility standards before and during the term.

Qualifications:
  • Required:
    • Advanced degree (Masters or Ph.D) in Computer Science, Data Science, or Software Engineering or AI Related fields.
    • Experience applying LLMs in Enterprise or Analytics contexts, including prompt engineering, model evaluation, hallucination mitigation, and responsible deployment of LLM-Based systems for analytics and or decision support.
    • At least 1 year of teaching or training experience (preferably online/asynchronous)
    • Experience with online instruction
    • Excellent communication and teaching skills in an online learning environment.
  • Preferred:
    • Prior online teaching experience at the graduate level
    • Knowledge of global learner personas and culturally responsive pedagogy
    • Familiarity with Moodle LMS and digital authoring tools (e.g., H5P)

Interested candidates should submit:
A cover letter highlighting relevant qualifications and teaching experience.
A current CV or resume.
Contact information for three professional references.
Application review begins June 1, 2026 though we will continue to accept submissions on an ongoing basis.
This appointment is to a position that is in a collective bargaining unit represented by SEIU Local 509.
Compensation for this positon is: $6573.15
Pay Range Disclosure
The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.
Equal Opportunity Statement
Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").

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