Log In
Sign Up
Part-Time Data Science & AI Instructor (Hyderabad)
upGrad is expanding its Offline Learning Centres, and we are looking for a dynamic, part-time Data Science Instructor in Hyderabad who is well-versed in cutting-edge technologies like Generative AI and Agentic AI.
If you want to balance your current professional commitments while mentoring ambitious students and working professionals in a classroom setting, this is the perfect role for you!
Type: Part-Time
Location: Hyderabad (In-person classroom delivery)
Schedule: Weekend / Evening batches
Key Responsibilities
As a Part-Time Instructor, you will play a vital role in ensuring high-quality learning outcomes:
Deliver High-Impact Sessions: Conduct engaging, in-person lectures and hands-on training sessions in Data Science, Machine Learning, Deep Learning, and cutting-edge GenAI/Agentic AI frameworks.
Project Mentorship: Guide learners through real-world case studies, industry projects, and standard practical tools to ensure career readiness.
Collaborative Support: Work alongside Centre Managers and academic teams to track learner progress, resolve doubts, and offer constructive feedback.
Stay Cutting-Edge: Continuously update your practical knowledge to ensure our learners are trained on the latest industry trends and tools.
Skills & Experience Required
Experience: Minimum 2+ years of teaching, training, or core industry experience in Data Science and Machine Learning.
Core Technical Skills: Strong programming proficiency in Python, SQL, and Excel.
Advanced ML/DL: A solid grasp of classical ML/DL concepts (Regression, Decision Trees, Random Forests, Neural Networks, NLP, etc.).
AI Specialization: Practical exposure or strong theoretical foundation in Generative AI (LLMs, Prompt Engineering, RAG) and Agentic AI frameworks (LangChain, CrewAI, AutoGen, or similar).
Communication: Exceptional presentation, mentoring, and communication skills, with the ability to simplify complex technical architectures.
Education: BE/B.Tech (minimum); Postgraduation preferred.
