Contribute to the design and implementation of state-of-the-art AI solutions.
Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.
Collaborate with stakeholders to identify business opportunities and define AI project goals.
Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.
Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.
Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities.
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Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs.
Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.
Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly.
Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency.
Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases.
Ensure compliance with data privacy, security, and ethical considerations in AI applications.
Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications.
Generative AI