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 problems
- Developing 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.