Develop and apply Large Language Models (LLMs) in quantitative finance to power an AI hedge fund
Requirements
- PhD in Machine Learning, Computer Science, or a related field
- Extensive hands-on experience in LLM development and fine-tuning, using PyTorch, Hugging Face, or similar frameworks
- Deep understanding of LLM architectures and large-scale data processing pipelines
- Proven ability to translate cutting-edge AI research into real-world applications beyond theory
Responsibilities
- architect, fine-tune, and push the frontier of LLMs for financial applications
- Fine-Tuning on Financial Corpora: Adapt pre-trained LLMs to custom-built financial datasets which predict the market
- Leveraging Common Crawl Data: Develop robust data pipelines to process and integrate large-scale web data, enriching our models with diverse, real-world information
- Modifying LLM Architectures: Experiment with adjustments to LLM architectures and training algorithms to enhance performance in financial contexts
Other
- Location: San Francisco
- Compensation: $300k-$350k + incentives + usual benefits + flexible paid vacation
