Sr. AI Specialist

SR. AI SPECIALIST Location: Pune Company: Sonata Software JOB DESCRIPTION/ SKILL SET: · AI/ML, LLMs, advanced AI engineering Notes : LLMs, ML engineering Machine Learning, Deep Learning, Natural Language Processing, Gen-AI and Agentic AI systems. • Machine Learning, Deep Learning, Natural Language Processing, Gen-AI and Agentic AI systems. • Specialized in building end-to-end AI solutions, including data preprocessing, model development, · evaluation, and deployment in production environments. • Expertise in developing scalable LLM-powered applications, including RAG architectures, end-to-end NLP · pipeline and conversational Chatbot using GPT-based models. • Worked extensively with vector databases and embedding pipelines for semantic search and knowledge · retrieval systems. • Developed scalable Conversational AI systems for financial and enterprise use cases using GPT-4o and · LangChain-based architectures. • Proficient in Python and popular data science libraries (Pandas, NumPy, Scikit-learn, TensorFlow) for · data analysis and model development. • Skilled in extracting insights from data, including NLP techniques with transformer models (e.g., · BERT) for customer feedback analysis. • Collaborated with cross-functional teams to translate business requirements into robust AI solutions, · ensuring high data quality and model performance. Experienced with Agile methodologies and building · RESTful APIs (Flask, FastAPI) for deploying machine learning models • Strong problem-solving skills and a track record of delivering actionable data-driven solutions. TECHNICAL SKILLS • Generative AI: LangChain, LangGraph, OpenAI, Prompt Engineering, RAG, HuggingFace GPT, BERT, LLMs. • Machine Learning: Linear & Logistic Regression, Naïve Bayes, KNN, Decision Tree, K-Means Clustering. • Deep Learning: ANN, RNN, LSTM, Transfer Learning, Transformers. • Natural Language Processing: TF-IDF, NER, Sentiment Analysis, Word2Vec, Text Classification, • Tokenization, Text Summarization, Embeddings, Stemming & Lemmatization. • Libraries/Tools: Pandas, Numpy, Scikit-learn, TensorFlow, Keras, Matplotlib, Seaborn, PyTorch, Pydantic • Programming Language: Python, SQL • Statistical Methods: Predictive Analysis, Descriptive Statistics, PCA. • Vector Database/DB: Azure AI Search (Azure Cognitive Search), Weaviate, FAISS, Azure • Blob Storage. • Web Development & APIs: Angular, ReactJs , Flask, FastAPI • Deployment: CI/CD Pipeline, Docker • Cloud: Azure/AWS (Azure OpenAI Service, Bedrock)