Bloomberg - New York, NY
posted 4 months ago
Bloomberg's Engineering AI department is at the forefront of innovation, with over 300 AI practitioners dedicated to building highly sought-after products and features that often require novel innovations. We are investing in AI to enhance search, discovery, and workflow solutions using cutting-edge technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. As we expand our group, we are seeking highly skilled individuals to join our teams of Machine Learning (ML) and Software Engineers, who are responsible for delivering innovative solutions to AI-driven customer-facing products. At Bloomberg, we are committed to fostering a transparent and efficient financial marketplace. Our technology underpins a vast array of services, making news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across global capital markets. Since 2009, we have been developing Artificial Intelligence applications that provide high accuracy and low latency solutions to complex problems. Our AI systems are designed to process and organize the ever-increasing volume of structured and unstructured information necessary for informed decision-making. By leveraging AI, we uncover signals, produce analytics about financial instruments across all asset classes, and deliver clarity to our clients when they need it most. As a Senior Machine Learning Engineer in the AI Group, you will have the opportunity to collaborate with colleagues on production systems, writing, testing, and maintaining production-quality code. You will design, train, experiment, and evaluate ML models, algorithms, and solutions, demonstrating technical leadership by owning cross-team projects. Staying current with the latest research in ML, you will incorporate new findings into our models and methodologies. Additionally, you will represent Bloomberg at scientific and industry conferences and in open-source communities, and publish product and research findings in documentation, whitepapers, or leading academic venues.