Responsibilities
• Data collection and preparation: Collect and prepare data for training and evaluating LLMs. This may involve cleaning and processing text data, or creating synthetic data • Model development: Design and implement LLM models. This may involve choosing the right architecture, training the model, and tuning the hyperparameters • Model evaluation: Evaluate the performance of LLM models. This may involve measuring the accuracy of the model on a held-out dataset, or assessing the quality of the generated text • Model deployment: Deploy LLM models to production. This may involve packaging the model, creating a REST API, and deploying the model to a cloud computing platform. • Responsible AI: Should have proficient knowledge in Responsible AI and Data Privacy principles to ensure ethical data handling, transparency, and accountability in all stages of AI development. Must demonstrate a commitment to upholding privacy standards, mitigating bias, and fostering trust within data-driven initiatives. • Experience in working with ML toolkit like R, NumPy, MatLab etc.. • Experience in data mining, statistical analysis and data visualization
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