Extensive hands-on experience of frameworks and libraries:
Proficient in scikit-learn and SciPy for ML algorithms
Hands-on experience within python with PyTorch and experience in developing enterprise python applications
Skilled in natural language processing tasks (entity recognition, tokenization etc)
Strong knowledge of API/Microservices, Async programming, multithreading, performance, reliability, caching, event driven design, data pipelines, workflows, queues
Hands-on with Amazon SageMaker for building, training, and deploying scalable machine learning models in cloud.
Experience of Building rapid applications using FastAPI and Streamlit, Matplotlib, seaborn enabling prototyping.
Good understanding of Software Engineering, Architecture, testing, code quality principles and test driven development (TDD)
Must Have:
Generative AI & LLMs
Proficient in context-aware prompts to drive optimal performance from LLMs for summarization, reasoning, extraction, and classification tasks.
Hands-on experience in designing intelligent retrieval pipelines that combine vector databases like FAISS with semantic search mechanisms.
Should have Developed intelligent agents capable of reasoning, planning, and tool use by leveraging frameworks such as ReAct, LangChain/Langgraph.
Experience of Clustering techniques and classification models
TPBN1_UKTJ