at KPMG India
Full TimeRoles & responsibilities
— Leverage data-driven techniques to design, develop and improve Generative AI models, drawing on expertise in areas such as machine learning, deep learning, and statistics
— Utilizing Python for building high-quality GenAI systems. Expert level skills in using Python libraries and frameworks such as NumPy, Pandas, PyTorch / TensorFlow, Llamachain, and LangChain. Strong development experience in using LLMs, preferably GPT4 and Llama2 LLMs. Strong experience on Embedding methods.
— A strong optimization and fine-tuning LLMs / Embedding and LLM Evals required
— Build and maintain robust data pipelines: responsible for collecting, cleaning, processing, and transforming raw data into the usable format for the Generative AI models.
— Running rigorous testing and validation of the models to ensure accuracy, quality, and generalization of the models on unseen datasets.
— Staying abreast of the latest developments in the fields of Data Science, AI and Machine Learning in order to continually improve the project's methodologies and outputs.
— Presenting complex results in a clear and concise manner to stakeholders with different backgrounds, and advising on the best strategies based on the model's findings.
— Ensure that all models and algorithms developed adhere to KPMG standards and best practices, and comply with all relevant regulatory and company privacy policies.
Roles & responsibilities
— Leverage data-driven techniques to design, develop and improve Generative AI models, drawing on expertise in areas such as machine learning, deep learning, and statistics
— Utilizing Python for building high-quality GenAI systems. Expert level skills in using Python libraries and frameworks such as NumPy, Pandas, PyTorch / TensorFlow, Llamachain, and LangChain. Strong development experience in using LLMs, preferably GPT4 and Llama2 LLMs. Strong experience on Embedding methods.
— A strong optimization and fine-tuning LLMs / Embedding and LLM Evals required
— Build and maintain robust data pipelines: responsible for collecting, cleaning, processing, and transforming raw data into the usable format for the Generative AI models.
— Running rigorous testing and validation of the models to ensure accuracy, quality, and generalization of the models on unseen datasets.
— Staying abreast of the latest developments in the fields of Data Science, AI and Machine Learning in order to continually improve the project's methodologies and outputs.
— Presenting complex results in a clear and concise manner to stakeholders with different backgrounds, and advising on the best strategies based on the model's findings.
— Ensure that all models and algorithms developed adhere to KPMG standards and best practices, and comply with all relevant regulatory and company privacy policies.
