Senior Language Modeling Engineer - Artificial Intelligence

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.

The advent of large language models (LLMs) presents new opportunities for expanding our NLP capabilities with new products. This would allow our clients to ask complex questions in natural language and receive insights extracted across our vast number of Bloomberg APIs or from potentially millions of structured and unstructured information sources. 

Broad areas of applications and interest include: pretraining and fine-tuning methods for LLMs, efficient methods for training, multimodal models, learning from feedback and human preferences, retrieval-augmented generation, summarization, semantic parsing and tool use, domain adaptation of LLMs to financial domains, dialogue interfaces, evaluation of LLMs, model safety and responsible AI.

• Collaborate with colleagues on building and applying LLMs for production systems and applications
• Write, test, and maintain production quality code
• Train, tune, evaluate and continuously improve LLMs using large amounts of high-quality data to develop state-of-the-art financial NLP models
• Demonstrate technical leadership by owning cross-team projects
• Stay current with the latest research in AI, NLP and LLMs and incorporate new findings into our models and methodologies
• Represent Bloomberg at scientific and industry conference and in open-source communities
• Publish product and research findings in documentation, whitepapers or publications to leading academic venues

• Practical experience with Natural Language Processing problems, and a familiarity with Machine Learning, Deep Learning and Statistical Modeling techniques
• 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 experience
• Experience with Large Language Model training and fine-tuning frameworks such as PyTorch, Huggingface or Deepspeed
• Proficiency in software engineering
• An understanding of Computer Science fundamentals such as data structures and algorithms and a data oriented approach to problem-solving
• Excellent communication skills and the ability to collaborate with engineering peers as well as non-engineering stakeholders.
• A track record of authoring publications in top conferences and journals is a strong plus

Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or maternity/parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law. 

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