AI/ML Engineering Instructor

About the Role

Transfotech Academy is seeking an experienced AI/ML Engineering Instructor to lead our hands-on, career-focused AI/ML Engineering program. The instructor will deliver a 7-module curriculum covering foundational ML, NLP, Agentic AI, RAG, Big Data, and Cloud/MLOps, guiding students from core concepts to building real production-grade AI systems in a Capstone Project.

Key Responsibilities

• Design, deliver, and continuously update lectures, labs, and assignments across all 7 modules (Foundations of AI/ML, ML Algorithms, NLP, Agentic AI, RAG, Big Data, Cloud/MLOps)
• Provide 100% hands-on instruction using real datasets, tools, and frameworks (Python, Pandas, NumPy, Scikit-learn, XG Boost, Lang Chain, LlamaIndex, PySpark, Docker, Kubernetes, etc.)
• Guide student teams through the Capstone Project (e.g., churn prediction systems, RAG knowledge assistants, fraud detection pipelines, autonomous AI agents)
• Teach and mentor students on LLM APIs (OpenAI, Anthropic, HuggingFace), prompt engineering, vector databases, and multi-agent frameworks (LangChain Agents, CrewAI, AutoGPT)
• Cover cloud AI/ML deployment across AWS, Azure, and GCP, including CI/CD, model monitoring, and MLOps best practices
• Evaluate student progress through projects, assessments, and code reviews; provide actionable feedback
• Stay current with evolving AI/ML tools, frameworks, and industry practices to keep curriculum relevant
• Support career-readiness efforts, including portfolio reviews and technical interview preparation
• Collaborate with academic staff to refine course structure and improve learning outcomes

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or a related field (PhD is a plus)
• 3+ years of professional experience as an AI/ML Engineer, Data Scientist, or MLOps Engineer
• Strong proficiency in Python and ML libraries (NumPy, Pandas, Scikit-learn, XGBoost/LightGBM)
• Practical experience with NLP, Transformers, and LLM APIs (OpenAI, Anthropic, HuggingFace)
• Experience building Agentic AI and RAG systems (LangChain, LlamaIndex, vector databases such as FAISS, Pinecone, ChromaDB, or Weaviate)
• Familiarity with Big Data tools (Spark/PySpark, Kafka, Hadoop ecosystem)
• Hands-on experience with cloud AI/ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI) and containerization (Docker, Kubernetes)
• Prior teaching, training, mentoring, or technical workshop experience preferred

Preferred Qualifications

• Experience deploying production ML pipelines end-to-end
• Familiarity with CI/CD for ML and model versioning/monitoring
• Excellent communication skills with the ability to simplify complex AI concepts for learners at varying levels
• Passion for education and mentoring the next generation of AI/ML engineers.

What We Can Offer You

• Competitive compensation, commensurate with experience
• Flexible scheduling (aligned with 18-week intensive or part-time cohort formats)
• Opportunity to shape a growing, industry-aligned AI/ML curriculum
• Collaborative environment with expert instructors and career-services teams.