AI & Ml Technical Trainer

19 hours ago

Hyderabad, India ExcelR Full time

Job description :

ExcelR is seeking experienced AI and Machine Learning trainers to deliver a comprehensive AI and Machine Learning curriculum. The training program will span 40 working days, with daily classes of 5–6 hours, tentatively from August 20, 2025, to October 21, 2025. The role involves teaching theoretical concepts, guiding hands-on projects, and mentoring students on real-world AI/ML applications.

Skills Required :

Foundational ML: Logistic Regression, SVM, Decision Trees, Ensemble Methods (Bagging, Random Forests), Boosting (Gradient Boosting, AdaBoost, XGBoost, LightGBM), PCA, Clustering (K-means, Hierarchical, DBSCAN), Market Basket Analysis, and Recommendation Systems.

Deep Learning: ANN, CNN, RNN, LSTM, GRU, Transformers, GANs, Autoencoders, Diffusion Models (Stable Diffusion), and LLMs (e.g., GPT, BERT).

Data Preprocessing: Standardization, normalization, encoding, train-test split, cross-validation, regularization (Lasso, Ridge, ElasticNet), and feature engineering.

Generative AI: Text-to-image/audio/video generation, chatbots, sentiment analysis, and Retrieval-Augmented Generation (RAG) with FAISS.

Web & Cloud Deployment: Building and deploying RESTful APIs using Flask/FastAPI, cloud computing with AWS (EC2, S3, Lambda) and Azure (Blob, App Services), and Streamlit for project deployment.

Mathematics: Calculus, vector algebra, probability.

Prompt Engineering: Zero-shot, few-shot, prompt tuning, and designing effective prompts.

Case Studies: Hands-on projects (e.g., Bangalore housing prices, Breast cancer classification, Sales dataset).

Qualifications :

Education: Bachelor's/Master's in Computer Science, AI, ML, or related fields.

Experience: 3–5 years in Machine Learning, Deep Learning, and Full Stack AI development, with hands-on experience in:

Python and libraries like scikit-learn, TensorFlow, Keras, PyTorch.

Generative AI (GANs, Diffusion Models, LLMs like GPT-2, LLaMA).

Web development (Flask, FastAPI) and cloud deployment (AWS EC2, Azure).

Tools like Hugging Face, FAISS, LangChain, and Streamlit.

Teaching Skills: Prior teaching/training experience preferred, with the ability to explain complex topics (e.g., attention mechanisms, PCA) to undergraduate students.

Certifications: Relevant certifications in AI/ML (e.g., AWS Certified Machine Learning, Google Professional ML Engineer) are a plus.

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