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Job highlights

• Regularly review and fine-tune Large Language Models (LLMs) to ensure maximum accuracy and relevance for custom datasets

• Collect and prepare data for training and evaluating multimodal foundation models, including data cleaning and synthetic data creation.

• Develop and optimize large-scale language models such as GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders).

• Work on tasks involving language modeling, text generation, understanding, and contextual comprehension.

• Regularly review and fine-tune Large Language Models (LLMs) to ensure maximum accuracy and relevance for custom datasets.

• Build and deploy AI applications on cloud platforms like Azure, GCP, or AWS.

• Integrate AI models with company data to enhance and augment existing applications. Cognizant Careers+1Cognizant Careers+1 GrabJobs+3Cognizant Careers+3Cognizant Careers+3

Role & Responsibility:

• Handle data preprocessing, augmentation, and generation of synthetic data.
• Design and develop backend services using Python or .NET to support OpenAI-powered solutions or other LLM solutions.
• Develop and maintain AI pipelines.
• Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models

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