About Bloomberg's CTO Office
Bloomberg's CTO Office is the future-looking technical and product arm of Bloomberg L.P. We envision, design, and prototype the next generation infrastructure, hardware, and applications for the Bloomberg Terminal. Our projects include machine learning-powered products, cloud computing infrastructure and strategy, open source stewardship, natural language processing, and more. We are passionate about what we do.
What We Do
Bloomberg is looking to use code generation to revolutionize how engineers write code and how clients interact with its data. The recent advances in generative AI for code generation have demonstrated its opportunities to assist a developer's daily life by automating repetitive tasks, reducing errors, and increasing productivity. Bloomberg employs thousands of developers and data scientists whose experience can be improved through the use of these technologies. Moreover, Bloomberg offers access to millions of documents and structured data items through its proprietary APIs that we can help clients access through more natural interactions.
Bloomberg has been applying machine learning and natural language processing to deliver the best interaction with financial data possible, and has built up a strong engineering, product, and research culture to support this work. The Language Language Model Code Product Manager in the office of the CTO will lead our efforts to leverage language models to generate code in a variety of products across the company. This will be done by working on strategic research and bringing that work to clients through product development. Examples of applications include the test case generation, autocomplete for interactive compute notebooks, and the creation of configuration files.
What's in it for you:
The ideal candidate will be a senior researcher and/or product manager, with many years of expertise across multiple disciplines including academic research and publishing, product management, and people management. They will have the technical depth to partner with engineers on crucial emerging technologies (e.g., large transformer-based language models or, more generally, deep learning models). They will also have excellent collaboration skills that will enable them to work with stakeholders across the organization and responsively address emerging business challenges. They are expected to serve as a representative for the office of the CTO internally to product management and engineering teams and externally to academic partners, industry counterparts, and clients. Bloomberg values our deep engagement in academic conferences and in the open-source community, and an ideal candidate would lead our efforts in both spaces.
An ideal candidate will thrive in an environment where they can develop a strategic vision and see it realized through their technical expertise, focus, and partnership across the organization in order to bring value to clients.
Responsibilities
- Partner across the organization to develop a long-term strategy and identify use cases to leverage LLMs to generate code.
- Guide our research efforts in code generation to deliver scientific breakthroughs.
- Serve as a deep technical expert consultant around language modeling.
- Form relationships internally and externally to grow our network and knowledge.
- Set product priorities and ensure delivery for key strategic projects.
- Grow our internal code generation expertise, through people development, infrastructure development, mentorship and education (e.g., through https://bloomberg.github.io/foml and https://techatbloomberg.com/ai).
Requirements
- 5 + years of experience in a product focused research role
- Ph.D. or equivalent experience in code synthesis, information retrieval, natural language processing, and/or deep learning research.
- Several publications on applied aspects of LLMs or related technologies (e.g. ways to use models, finetuning, prompt engineering, interaction with LLMs).
- Record of working with cross-functional teams developing successful products.
- Excellent communication and collaborative skills.
- Blend of long-term strategic vision with goal-driven tactical focus.
- Commitment to grow an inclusive and diverse environment.
- Engagement with the research community (e.g., conference or workshop service).