LLM Finetuning
1 month ago
About Awign Expert:
Job Title: LLM Finetuning
Experience: 4-5 years
Joining: Immediate
Location: Remote
Responsibilities -
- Evaluating and selecting the open source and/or commercial LLMs suitable for finanical lending domains
- Finetune the selected models for domain-specific tasks
- Continuously monitor and measure model performance and improve model performance
- Build and Manage model pipeline lifecycle - from getting datasets, cleaning datasets, finetuning the models,measure model performance,deploy the models,monitor and improve the model performance to meet business needs.
Essential Skills:
Python Programming: Proficiency in Python,
Working with libraries like TensorFlow, PyTorch,Transformers,NLTK,Pandas,sklearn, and other related libraries used in NLP tasks and finetuning language models.
Experience with building comperehnsive python modules for NLP tasks like tokenization, word embeddings,classifications etc…
Proficiency in data preprocessing techniques such as text cleaning, tokenization, normalization,handling of special characters is essential for preparing data for finetuning language models.
Knowledge of machine learning concepts like neural networks, optimization algorithms, model evaluation techniques.
Deep learning expertise w.r.t NLP
Expertise on adapting pre-trained langugae models to specific tasks and domains
Experience with hyperparameter tuning methods such as grid search, random search, or Bayesian optimization for optimizing model performance during finetuning.
Experience in financial lending domain customer onboarding, loan servicing, collections.
Experise with 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, such as bias mitigation, privacy preservation, and responsible AI practices
Ability to work with existing customer systems.
Requirements
Requirements
Python, LLM, Fine-Tuning
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