Subject Matter Expert (SME) AI Engineering and Deployment Graduate Certificate

Program Overview:

The AI Engineering and Deployment Graduate Certificate is a specialized, four-course program focused on the practical application, deployment, and integration of AI and ML systems in engineering environments. The SME will lead the development of academically rigorous and industry-aligned content, including syllabus design, instructional materials, and assessments.

Key Responsibilities

As the Subject Matter Expert, you will:

• Curriculum Development

• Design and structure the syllabus for the following graduate-level modules:
  • PE AI 600 – Applied Machine Learning & AI Fundamentals (v2)
  • PE AI 610 – Deep Learning & Generative AI
  • PE AI 620 – MLOps & AI Systems for Engineers
  • PE AI 630 – AI Applications Capstone: Integration & Specialization
• Align course content with the latest academic standards, industry practices, and learning outcomes.
• Integrate hands-on, project-based learning to simulate enterprise-level AI deployment.

• Content Creation

• Create structured lesson plans, readings, coding exercises, labs, and industry case studies.
• Provide datasets, notebooks (e.g., Jupyter), and cloud-based deployment templates as needed.
• Design modular content that can be reused across programs and easily tagged for search and retrieval.
• Document skills and competencies for each module and apply SEO-style tags for future indexing in a central content database.
• Use institutional blueprint templates to align learning outcomes, competencies, and content duration per module.

• Assessment Design

• Create formative and summative assessments, including: Assignments, quizzes, Capstone projects
• Develop grading rubrics and model answers.

• Collaboration & Iteration
• Collaborate with instructional designers and program stakeholders to review and refine deliverables.
• Participate in periodic SME review meetings and address academic board feedback.
• Stay updated on emerging trends in ML, MLOps, and Generative AI.

Qualifications:

Education

• Master’s or Ph.D. in Artificial Intelligence, Machine Learning, Data Science, Computer Engineering, or a closely related field.

Professional Experience

• 10+ years of experience in applied AI/ML development or deployment.
• Holds a mid-to-senior-level management role — with proven ability to provide strategic insights on AI integration, systems design, and program development.
• Hands-on experience with:
  • Deep learning (e.g., TensorFlow, PyTorch)
  • Generative AI tools (e.g., LLMs, GANs, diffusion models)
  • MLOps stacks (e.g., MLflow, Kubeflow, AWS Sagemaker, Azure ML)
  • AI system integration in real-world engineering contexts
  • Is recognized as a thought leader — has shared expertise through public talks, open-source contributions, or published articles to build program credibility and visibility.

Preferred Skills

• Experience designing and delivering academic programs or corporate training in AI/ML.
• Involvement in AI solution deployment in enterprise or high-tech environments.
• Experience mentoring capstone or applied research projects.

Key Skills

• Python programming and ML libraries (Scikit-learn, XGBoost, Hugging Face)
• Knowledge of containerization (Docker), orchestration (Kubernetes), and CI/CD workflows
• Familiarity with version control, data pipelines, and cloud infrastructure
• Strong technical writing and instructional communication skills

You must take the necessary steps to safeguard the integrity, security, and confidentiality of shared confidential information.

For additional information on Hurix, please visit: https://www.hurix.com/life-at-hurix/