Data Science

Responsibilities : - design, development and implementation of NLP projects and solve complex business problems.. Well versed with Artificial Intelligence, Machine Learning and Deep Learning algorithms and techniques. Evaluating and selecting appropriate machine learning models for tasks, as well as building and training working versions of those models using Python and other open-source technologies Proven experience in developing and deploying NER models. Experience with transfer learning and pre-trained language models (e.g., BERT, GPT). Proficiency in programming languages such as Python, with experience in NLP libraries (e.g., spaCy, NLTK, Stanford NLP, Hugging Face Transformers). Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch, Keras, scikit-learn, Caffe, CNTK Working across client teams to develop and implement LLM solutions. Develop prompts that instruct LLM to generate relevant and accurate responses, RAG Architecture, LLM Fine Tuning Expertise in EDA, data engineering, including data curation, cleaning, and preprocessing. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Track record of driving innovation and staying updated with the latest AI research and advancements