The Senior LLM Research Engineer will join Bloomberg's Engineering AI department, focusing on building innovative AI-driven customer-facing products. This role involves leveraging large language models to enhance natural language processing capabilities and improve search and discovery solutions. The engineer will collaborate with machine learning and software engineering teams to develop state-of-the-art financial NLP models. The position emphasizes technical leadership, research publication, and staying current with advancements in AI and NLP.

• Practical experience with Natural Language Processing problems and 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 with 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 and understanding of Computer Science fundamentals such as data structures and algorithms.
• Excellent communication skills and the ability to collaborate with engineering peers and non-engineering stakeholders.
• A track record of authoring publications in top conferences and journals is a strong plus.

• 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.
• Demonstrate technical leadership by owning cross-team projects.
• Stay current with the latest research in AI, NLP, and LLMs and incorporate new findings into 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.

• Bloomberg offers a comprehensive suite of benefits designed to support health, financial stability, and work-life balance.