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Hexware - Data Scientist - NLP/BERT/Generative AI


Hexaware


Location

Chennai | India


Job description

Job Description :- 5+ years of experience in the field of data science/ML production grade with exposure to ML algorithms like regression and tree-based models (At least 5 ML model built and at least 2 ML models deployed)- Good experience in prototyping with Generative AI models, with a strong understanding of deep learning techniques such as GPT/BERT (Q&A/Entity Extraction/Text Similarity/Text Summarization Models)- In-depth understanding of BERT embeddings and Word2Vec/Glove embeddings- Demonstrable solutions in the form of POC's, any cloud marketplace postings built using Generative AI with up to date on the latest trends in the Generative AI theme- Experimentation with Gen AI APIs (application programming interfaces) like Azure Open AI/Vertex AI PaLM API (application programming interfaces). - Good to have exposure in fine-tuning these API foundation models; is aware of the costing behind them (Ada/Babbage/Davinci/Text Bison Foundation Models) and aware of the governance/compliance behind using Generative AI models for the Business- Proficient in programming languages such as Python/R and Pyspark/Scala/Spark- Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or Keras, with a strong understanding of neural networks, architectures, and optimization techniques- Working knowledge in Deep Learning algorithms with different NN architectures like CNN (Convolution Neural Network), RNN, LSTM etc. with at least 1 model implementation- At least 2 years of domain experience and client facing experienceSecondary skills :- Familiarity with cloud platforms such as AWS, Azure, or GCP, and experience in leveraging distributed computing for large-scale model training and deployment- Knowledge of software development methodologies, such as Agile or Scrum- Excellent communication skills, with the ability to effectively convey technical concepts to both technical and non-technical stakeholders- Knowledge in SQL and AutoML (ref:hirist.tech)


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