Job Description

Overview:

we are looking for a strong ML/NLP/GenAI skills and are eager to work in a collaborative environment with global teams to drive NLP/GenAI application in business problems. You work independently and are always willing to learn new technologies. You thrive in a dynamic environment and are able to interact with various stakeholders and cross functional teams to implement data science driven business solutions.
Responsibilities:

Working in collaborative environment with global teams to drive AI solutioning of business problemsDeveloping end to end analytical solutions, and articulating insight findings to leadership. Provide data-driven recommendations to business by clearly articulating complex modeling concepts through generation and delivery of presentations. Analyzing and modeling both structured and unstructured data from a number of distributed client and publicly available sources. Designing and building scalable advanced NLP/SLM/LLM models to meet the needs of given Business engagement.

Requirements:

Experience in Machine Learning, Deep Learning model development & Deployment from scratch in Python.Strong Knowledge and hands-on experience on implementation of large-scale NLP Projects and Fine tuning & Evaluation of LLMs for downstream tasks such as text generation, Classification, summarization, question answering, entity extraction etc. Working knowledge of NLP frameworks and libraries like NLTK, Spacy, Transformers, Pytorch, Tensorflow, hugging face api's. Working knowledge about various Machine Learning Algorithms such as Supervised, Unsupervised, Generative AI . Should know the various data preprocessing techniques and its impact on algorithm's accuracy, precision and recall. Knowledge & Implementation Experience of Deep Learning i.e Convolutional Neural Nets (CNN), Recursive Neural Nets (RNN) & Long Short Term Memory (LSTM), Generative Adversarial Networks (GAN), Deep Reinforcement Learning. Experience with RESTful, JSON API services. Working knowledge on these: Word embeddings, TF-IDF, Tokenization, N-Grams, Stemmers, lemmatization, Part of speech tagging, entity resolution, ontology, lexicology, phonetics, intents, entities, and context. Experience in analyzing Live Chat/call conversation with agents. * Knowledge of Python, Sql, PySpark, Scala and/or other languages and tools.