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 practicesEvaluate student progress through projects, assessments, and code reviews; provide actionable feedbackStay current with evolving AI/ML tools, frameworks, and industry practices to keep curriculum relevantSupport career-readiness efforts, including portfolio reviews and technical interview preparationCollaborate with academic staff to refine course structure and improve learning outcomesRequired 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 EngineerStrong 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 preferredPreferred QualificationsExperience deploying production ML pipelines end-to-endFamiliarity with CI/CD for ML and model versioning/monitoringExcellent communication skills with the ability to simplify complex AI concepts for learners at varying levelsPassion for education and mentoring the next generation of AI/ML engineers.What We Can Offer You Competitive compensation, commensurate with experienceFlexible scheduling (aligned with 18-week intensive or part-time cohort formats)Opportunity to shape a growing, industry-aligned AI/ML curriculumCollaborative environment with expert instructors and career-services teams.