Part-Time Online Course Facilitator Applied Machine Learning & Generative AI

Cornell University • Ithaca, NY

41d • Remote

About The Position

eCornell delivers expertly crafted online certificate programs designed by Cornell University faculty. Our facilitators play a central role in creating dynamic, engaging, and highly interactive learning experiences. We are committed to providing an exceptional student experience through live interactions, meaningful feedback, and authentic engagement. We are seeking experienced professionals to join our team as Course Facilitators in our Applied Machine Learning and AI portfolio, with a strong emphasis on generative AI and large language models (LLMs). Facilitators are not course authors or adjunct faculty but are vital to ensuring the effective delivery of content created by Cornell faculty. To be considered for this position, please include a cover letter with your application materials. In this role, you will complement our asynchronous course content by: Leading engaging live sessions that connect core ML concepts to modern generative AI and LLM applications. Providing personalized and constructive feedback (written and recorded video) on coding assignments, solution designs, and applied AI projects. Coaching learners on responsible, effective use of AI tools (including LLM-based systems) in real-world business and technical settings. Fostering meaningful connections with students in a highly interactive online environment. Program-Specific Focus We are currently seeking facilitators to support certificate programs across three primary focus areas. Candidates may be matched to one or more areas based on expertise. 1. AI for Business Impact (Non-Technical & Mixed Audiences) Courses in this track help business leaders and professionals understand how AI and generative AI can transform products, services, and operations—even if learners do not have a strong coding background. Ideal facilitator background: Ability to translate ML and LLM concepts into clear, accessible language for mixed technical/non-technical audiences. Experience identifying and scoping AI use cases (e.g., customer support automation, content generation, analytics workflows). Familiarity with data, model lifecycle, and implementation trade-offs so you can guide conversations about feasibility, risk, and ROI. Comfort discussing responsible AI, governance, bias, and organizational change management related to AI adoption. 2. Designing Applied AI & LLM Solutions (Solution & Product Focus) Courses in this track are geared toward professionals who want to design and configure AI solutions from the ground up—such as chatbots, assistants, and internal tools powered by LLMs. Ideal facilitator background: Hands-on experience designing and building AI-powered applications (e.g., LLM-based chatbots, retrieval-augmented generation systems, intelligent agents). Strong familiarity with prompt design, prompt chaining, and evaluation of LLM outputs in real workflows. Experience integrating AI/LLM APIs into applications (e.g., via Python, REST APIs, orchestration frameworks, or low-code/no-code platforms). Understanding of core concepts like vector databases, basic RAG patterns, and system / user / tool prompt structuring. 3. Advanced ML & LLM Engineering (Highly Technical) Courses in this track are designed for learners with strong technical backgrounds who want to deepen their skills in machine learning and modern foundation models. Ideal facilitator background: Deep expertise in machine learning and deep learning, including supervised/unsupervised learning, neural network architectures, and model evaluation. Strong understanding of LLMs and generative models (e.g., transformers, fine-tuning/PEFT, embeddings, evaluation metrics, and optimization strategies). Experience working with ML/LLM frameworks and infrastructure (e.g., TensorFlow, PyTorch, model deployment, monitoring, MLOps concepts). Ability to review and debug complex ML and LLM-related code, experiments, and pipelines submitted by learners.

Requirements

• Relevant graduate degree and 5+ years of relevant professional experience, or an equivalent combination of education and experience.
• Core technical foundation: Strong proficiency in Python. Familiarity with Jupyter notebooks and Git/GitHub. Comfortable reviewing and debugging ML-related code submitted by learners.
• Machine learning and AI expertise: Experience with core ML techniques: supervised and unsupervised learning, feature engineering, model evaluation/validation, and deployment concepts. Familiarity with common ML libraries: scikit-learn, pandas/numpy, matplotlib/seaborn.
• Generative AI / LLM experience (at least one of the following): Practical experience using or integrating LLMs (e.g., OpenAI, Anthropic, Azure/OpenAI, or open-source models). Experience designing prompts, evaluating LLM outputs, and using LLMs in real workflows (analysis, content generation, coding assistance, etc.). Experience building or supporting AI-powered products or internal tools that leverage LLMs or other generative models.
• Exceptional communication skills, both written and verbal. Ability to deliver authentic, concise, and impactful feedback to busy professionals.
• Proficiency with online learning tools (e.g., Canvas, Zoom) and comfort with technology for instruction Loom video submission with application

Nice To Haves

• Leadership or strategy advisory experience (e.g., guiding AI adoption, leading data/AI teams, or driving analytics initiatives).
• Advanced experience in at least one focus area (Business Impact, Solution Design, or Advanced Engineering) such as: Leading AI transformation initiatives or building AI roadmaps. Architecting and deploying LLM-powered solutions (e.g., RAG, agents, workflow automation). Advanced ML/LLM engineering, including experimentation, optimization, and model evaluation.
• Relevant certifications, such as: Google Professional Machine Learning Engineer AWS Machine Learning Specialty Azure AI Engineer or Data Scientist Associate Recognized ML/AI or generative AI specializations (DataCamp, Coursera, edX, etc.) IBM Machine Learning Professional Certificate TensorFlow Developer Certificate
• Previous experience in online instruction or facilitation, particularly with technical or AI-focused content.

Responsibilities

• Engage Students: Lead dynamic live discussions that foster interaction and deepen understanding.
• Provide Feedback: Deliver clear, constructive, and authentic feedback on student submissions, including recorded video responses.
• Facilitate Effectively: Manage online discussions, respond promptly to student inquiries, and track student progress.
• Commitment: Facilitate a minimum of 1-2 courses per month with consistent engagement and preparation.
• Onboarding and Training: Complete an in-depth onboarding program, including shadowing live courses, participating in debrief sessions, and mastering the assigned certificate program.
• Continuous Improvement: Engage in ongoing training and professional development to stay current with emerging learning methodologies, educational technologies, and best practices in online facilitation.

Benefits

• Comprehensive onboarding and training program to set you up for success.
• Access to ongoing professional development resources and periodic training updates.
• Opportunities to contribute to an exceptional online student experience.
• A collaborative and supportive facilitator community.

What This Job Offers

• Job Type: Part-time
• Career Level: Mid Level