Senior Applied AI Engineer - Artificial Intelligence

Details

Bloomberg’s Engineering AI department has more than 400 AI practitioners building products and features that require novel innovations. The team develops AI-powered search, discovery, and workflow solutions using transformers, gradient-boosted decision trees, large language models, and dense vector databases.

The role involves contributing to teams of machine learning and software engineers developing innovative solutions for AI-driven, customer-facing products. Bloomberg builds AI systems that process and organize structured and unstructured information, uncover signals, produce analytics for financial instruments, and support clients across global capital markets.

The team is seeking Senior Applied AI Engineers with strong expertise and passion for large language model research and applications. Areas of application include LLM application and fine-tuning methods, efficient training methods, multimodal models, learning from feedback and human preferences, retrieval-augmented generation, summarization, semantic parsing and tool use, financial-domain adaptation, dialogue interfaces, LLM evaluation, model safety, and responsible AI.

Responsibilities

• Collaborate with colleagues to build and apply LLMs for production systems and applications.
• Write, test, and maintain production-quality code.
• 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 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 at leading academic venues.

Requirements

• Practical experience with natural language processing problems and familiarity with machine learning, deep learning, and statistical modeling techniques.
• Ph.D. in machine learning, natural language processing, or a relevant field; or a master’s degree in computer science, machine learning, mathematics, statistics, engineering, or a related field with at least two years of relevant work experience.
• Experience with large language model training and fine-tuning frameworks such as PyTorch, Hugging Face, or DeepSpeed.
• Proficiency in software engineering.
• Understanding of computer science fundamentals, including data structures and algorithms, along with a data-oriented approach to problem-solving.
• 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.

Benefits

Benefits and total rewards may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, vision, short- and long-term disability benefits, a 401(k) match, life insurance, and wellness programs.

Salary range: $165,000–$260,000 USD annually, plus benefits and bonus. Actual compensation may vary based on geographic location, work experience, market conditions, education, training, and skill level.