Job Title: LLM Engineer (Fine-tuning)
Location: Remote
Experience: 5-8 years
Opportunity Type: Contract to hire (Contract Duration 3 Months)
**Note: This position is with one of our hiring partners
Role Overview:
As an LLM Fine Tuner, you will be responsible for evaluating, selecting, and fine-tuning open source and/or commercial Language Models (LLMs) for financial lending domains. You will work closely with our data scientists and engineers to build and manage model pipelines, continuously monitoring and improving model performance to meet business needs.
Key Responsibilities:
Evaluate and select LLMs suitable for financial lending domains.
Fine-tune selected models for domain-specific tasks, such as customer onboarding, loan servicing, and collections.
Build and manage model pipeline lifecycle, including data collection, cleaning, finetuning, deployment, monitoring, and performance improvement.
Develop comprehensive Python modules for NLP tasks, including tokenization, word embeddings, and classifications.
Implement data preprocessing techniques for text cleaning, tokenization, normalization, and handling of special characters.
Utilize machine learning concepts, neural networks, and optimization algorithms for model finetuning.
Adapt pre-trained language models to specific tasks and domains.
Conduct hyperparameter tuning using methods like grid search, random search, or Bayesian optimization.
Evaluate model performance using appropriate metrics and interpret model predictions.
Ensure ethical considerations related to language models, such as bias mitigation and privacy preservation, are addressed.
Collaborate effectively with existing customer systems to integrate and deploy models.
Essential Skills:
Proficiency in Python programming, with experience in libraries like TensorFlow, PyTorch, Transformers, NLTK, Pandas, and sklearn.
Deep learning expertise in NLP tasks.
Experience in the financial lending domain, including customer onboarding, loan servicing, and collections.
Familiarity with tools and frameworks for handling large datasets.
Strong knowledge of machine learning concepts and model evaluation techniques.
Ability to adapt pre-trained language models to specific tasks and domains.
Experience with hyperparameter tuning methods for optimizing model performance.
Awareness of ethical considerations in language models and responsible AI practices.
Additional Information:
Full-time remote opportunity.
Competitive salary and benefits package.
Opportunity to work with a dynamic and innovative team in a fast-paced environment.
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