Role overview
Bloomberg’s Engineering AI department has 400+ 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.
Responsibilities
- Collaborate with colleagues on production systems and write, test, and maintain production quality code
- Design, train, experiment, and evaluate ML models, algorithms and solutions
- Demonstrate technical leadership by owning cross-team projects
- Stay current with the latest research in AI 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
Basic qualifications
- Practical experience with Machine Learning problems, and a familiarity with Classical 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 previous relevant work experience
- 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