Senior Language Modeling Research Engineer - Artificial Intelligence

Bloomberg - New York, NY

Full-time - Senior

New York, NY

251-500 employees

Broadcasting and Content Providers

About the position

Bloomberg's Engineering AI department is at the forefront of innovation, with over 300 AI practitioners dedicated to developing cutting-edge products and features that leverage advanced technologies. We are committed to enhancing search, discovery, and workflow solutions through the use of transformers, gradient boosted decision trees, large language models (LLMs), and dense vector databases. As we expand our team, we are seeking highly skilled individuals to join our Machine Learning (ML) and Software Engineering teams, who will play a crucial role in delivering innovative AI-driven solutions for our customer-facing products. Since 2009, Bloomberg has been a pioneer in building Artificial Intelligence applications that provide high accuracy and low latency solutions to complex financial problems. Our AI systems are designed to process and organize vast amounts of structured and unstructured information, enabling our clients to make informed decisions based on real-time analytics about financial instruments across various asset classes. The introduction of large language models presents exciting opportunities to enhance our natural language processing (NLP) capabilities, allowing clients to interact with our systems using complex natural language queries and receive insights from our extensive Bloomberg APIs and data sources. We are particularly interested in candidates who have a strong background in LLM research and applications. The role involves exploring broad areas such as pretraining and fine-tuning methods for LLMs, efficient training techniques, multimodal models, and the integration of human feedback into model training. Additionally, responsibilities include developing dialogue interfaces, evaluating model performance, and ensuring the safety and ethical use of AI technologies. As a Senior LLM Research Engineer, you will collaborate with colleagues to build and apply LLMs in production systems, write and maintain high-quality production code, and continuously improve our financial NLP models using large datasets. You will also have the opportunity to demonstrate technical leadership by managing cross-team projects, staying updated with the latest research in AI and NLP, and representing Bloomberg at industry conferences. Publishing your findings in leading academic venues will also be a key aspect of this role.

Responsibilities

• 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 conferences and in open-source communities
• Publish product and research findings in documentation, whitepapers or publications to leading academic venues

Requirements

• 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

Nice-to-haves

• Experience with multimodal models
• Knowledge of retrieval-augmented generation
• Familiarity with summarization and semantic parsing techniques
• Experience in domain adaptation of LLMs to financial domains
• Understanding of model safety and responsible AI practices

Benefits

• Paid holidays
• Paid time off
• Medical insurance
• Dental insurance
• Vision insurance
• Short and long term disability benefits
• 401(k) with matching
• Life insurance
• Various wellness programs
• Merit increases
• Incentive compensation