LLM Finetuning

• Evaluate and select open source and/or commercial Language Models (LLMs) suitable for financial lending domains.
• Finetune selected models for domainspecific tasks ensuring optimal performance.
• Continuously monitor and measure model performance implementing improvements as needed.
• Build and manage the model pipeline lifecycle including acquiring datasets cleaning data finetuning models measuring performance deploying models monitoring and enhancing performance to meet business needs.
• Collaborate with crossfunctional teams to integrate LLM solutions into existing customer systems.

• Proficiency in Python programming with experience in TensorFlow PyTorch Transformers NLTK Pandas scikitlearn and related NLP libraries.
• Experience in developing comprehensive Python modules for NLP tasks such as tokenization word embeddings and classifications.
• Strong understanding of data preprocessing techniques for text data including cleaning tokenization normalization and handling special characters.
• Knowledge of machine learning concepts neural networks optimization algorithms and model evaluation techniques.
• Deep learning expertise in NLP including adapting pretrained language models to specific tasks and domains.
• Experience with hyperparameter tuning methods such as grid search random search or Bayesian optimization.
• Familiarity with the financial lending domain including customer onboarding loan servicing and collections.
• Proficiency in tools and frameworks for handling large datasets.
• Ability to evaluate model performance using appropriate metrics and interpret model predictions.
• Awareness of ethical considerations related to language models including bias mitigation privacy preservation and responsible AI practices.
• Ability to work with existing customer systems and integrate LLM solutions effectively.

nlp,python,tensorflow