Job Description
Bloomberg's Engineering AI department has 300+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products.At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions. Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.We are looking for Senior LLM Research Engineers with a strong expertise and passion for Large Language Modeling research and applications to join our team.
Responsibilities + Skills
Education
Collaborate with colleagues on building and applying LLMs for production systems and applicationsWrite, test, and maintain production quality codeTrain, tune, evaluate and continuously improve LLMs using large amounts of high-quality data to develop state-of-the-art financial NLP models
Experience
Ph.D. in ML, NLP or a relevant field or MSc in CS, ML, Math, Statistics, Engineering, or related fields and 2+ years of relevant work experienceExperience with Large Language Model training and fine-tuning frameworks such as PyTorch, Huggingface or DeepspeedProficiency in software engineeringAn understanding of Computer Science fundamentals such as data structures and algorithms and a data oriented approach to problem-solving
