Senior ML Research Engineer - Sustainable Finance
Location
London
Business Area
Engineering and CTO
Ref #
10052491
Description & Requirements
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.
Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions.
Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most. As an ML Research Engineer on the AI Sustainable Finance team, you will be working on exciting initiatives such as real-time controversies detection from news, greenhouse gas emissions estimation for global equities, financial materiality assessment of corporate conduct, and ML explainability for our sustainability solutions.
Bloomberg's sustainable finance solutions are built on comprehensive, reliable, and contextualized environmental, social, and governance data, helping investors see clearly and act with confidence. Our team powers the ML systems behind these solutions, enabling clients to surface opportunities in a shifting landscape, integrate sustainability signals into their models, manage risk exposure, and measure the impact of their strategies.
Join us as a Senior ML Research Engineer and you will have the opportunity to:
- Collaborate with sustainable finance domain experts to develop systems that identify, categorize, and assess sustainability risks
- Own cross-team projects end-to-end, from research and experimentation through production deployment
- Research and train ML models that help investors assess and manage sustainability risks
- Design and build real-time NLP pipelines using large language models
- Develop evaluation frameworks and annotation tooling that drives continuous model improvement
- Stay current with the latest research in NLP, LLMs, and estimation techniques, 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
We are looking for a Senior ML Research Engineer with the following experience:
- Experience building production ML systems, with exposure to sustainability and responsible investment problems
- Practical experience with Machine Learning problems and Large Language Models
- 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 with Python, including experience with production ML infrastructure (model serving, data pipelines, evaluation frameworks)
- Familiarity with LLM-based systems for structured information extraction from unstructured text
- 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 such as sustainable finance analysts, product managers, and domain experts
- Interest in sustainability or climate finance is a strong plus
- A track record of authoring publications in top conferences and journals is a strong plus
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