Lead Data Scientist - NLP/Generative AI

About the Lead Data Scientist (NLP & GenAI) Job Role - You will help our clients solve real-world problems by tracing the data-to-insights lifecycle: - Understand business problems, making sense of the data landscape & footprint, performing a combination of Gen AI , Advanced NLP, exploratory analysis- Create, experiment with and deliver innovative solutions in a consultative mindset to client stakeholders using textual data- Guide team of data scientists to offer exceptional solutions to clients, across domains. Work Location: Hyderabad/Bangalore (Hybrid mode with 3 days in office) Qualification and experience for the Lead Data Scientist (NLP) Role : - Background in Computer Science/Computer Applications or any quantitative discipline (Statistics, Mathematics, Economics/Operations Research etc.) from a reputed institute. - 5-8 years of experience using analytical tools/languages like Python on large-scale data - Must have Semantic model & NER experience - Experience working with pre-trained models, awareness of state-of-art in embeddings and applicability for use cases - Must have strong experience in NLP/NLG/NLU applications using any popular Deep learning frameworks like PyTorch, Tensor Flow, BERT, GPT (or similar models)- Demonstrated ability to engage with client stakeholders at multiple levels and provide consultative solutions across different domains - Deep knowledge of techniques such as Linear Regression, gradient descent, Logistic Regression, Forecasting, Cluster analysis, Decision trees, Linear Optimization, Text Mining- Strong understanding of integrating NLP models into business workflows. Prospect should have exposure to project initiation to business impact creation in at least one project. - Experience in productionizing & retraining models - Ability to guide and mentor teams of associates on solution development and approaches - Broad knowledge of fundamentals and state-of-the-art in NLP and machine learning - Coding skills in one or more programming languages such as Python, SQL - Expert / high level of understanding on language semantic concepts & data standardization - Proven track record of successful models and practical implementation- Experience in training transformer-based language models and their variants (T5, BART, BERT etc)- Knowledge of transformer architecture and the impacts of modifying the same- Familiar with multiple evaluation metrics fore LLMs- Experience with Huggingface, Langchain etc., building the pipelines- Experience with Vector DBs, Text embedding models- Different prompting templates Zero-shot, Few-shot, Composition etc.- LLM In-context learning , Fine tuning, Model evaluation metrics etc. - Text pre/post - processing techniques- Experience in using GPUs to train deep learning models- Good knowledge of solving industrial problems using deep learning models with NLP-related use-cases- Familiar with all prompting techniques - Hands-on experience with popular ML frameworks such as Pytorch (must), TensorFlow - Experience with Production deployment of LLM solutions- Building scalable LLM solutions- Familiarity with any Cloud services such as Azure ML studio, AWS Sage Maker etc. is considered a plus - Knowledge in Machine Learning techniques in entity resolution, common speech products or text search domain (ref:hirist.tech)