Factentry - Lead Data Scientist - Generative AI in भारत

Job Summary :We are looking for an experienced AI - Generative AI Developer who can work across the AI spectrum - from classical machine learning models to cutting-edge Generative AI https://jobeax.com/link/uTkIfl1tAHKRWQPa role demands strong experience in building ML models using regression, classification, and tree-based algorithms, along with hands-on exposure to LLMs and generative frameworks like GPT, Stable Diffusion, and https://jobeax.com/link/714mI5EptknyNdk8 AI/ML Responsibilities :- Design and implement supervised and unsupervised ML models including Linear Regression, Logistic Regression, Decision Trees, Random Forest, XGBoost, Naive Bayes, K-Means, SVM, PCA, etc.- Preprocess and analyse structured/tabular datasets.- Evaluate models using metrics like accuracy, precision, recall, ROC-AUC, and RMSE.- Build predictive models, deploy them into production, and monitor performance.- Collaborate with business teams to translate requirements into ML use https://jobeax.com/link/bk6gow4ZjVY9kQRQ AI (GenAI) Responsibilities :- Build and fine-tune LLMs (e.g., GPT, LLaMA, PaLM) for summarisation, Q&A, document generation, etc.- Implement prompt engineering, RAG pipelines, and vector database integrations.- Use libraries like Hugging Face Transformers, LangChain, and LlamaIndex.- Develop APIs to expose GenAI models in real-time apps.- Optimise model inference using quantisation, batching, etc.- Ensure safe, explainable, and bias-free output in alignment with AI ethics https://jobeax.com/link/73EKYPsUaH5O0c6y :- Bachelor's or Master's in Computer Science, Data Science, Statistics, or related field.- Strong programming skills in Python, with experience in NumPy, Pandas, Scikit-learn.- Proficiency in classical ML algorithms (regression, trees, naive Bayes, etc.).- Experience with LLM frameworks like OpenAI API, Hugging Face, and LangChain.- Understanding of transformer architecture, NLP, embeddings, and tokenisation.- Familiarity with REST API development using FastAPI/Flask.- Exposure to cloud platforms (AWS/GCP/Azure) and Docker/Kubernetes.Preferred Skills :- Experience with deep learning (TensorFlow, PyTorch).- Exposure to image/audio/video generation using models like DALL-E, Stable Diffusion, Whisper.- Familiarity with RAG, LLMOps, and vector stores (FAISS, Pinecone, Weaviate).- Knowledge of MLOps pipelines, model monitoring, and CI/CD for ML. (ref:hirist.tech)