Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
Algorithms @ 4
Data Structures @ 4
Java @ 7
LLM
Machine Learning
Mathematics @ 4
Python @ 7
Technical Leadership
Vector Databases
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Bloomberg’s Engineering AI department has more than 400 AI practitioners building products and features that require novel innovations. The group develops AI-powered search, discovery, and workflow solutions using transformers, gradient-boosted decision trees, large language models, and dense vector databases.
Bloomberg builds technology that makes news, research, financial data, and analytics on more than 35 million financial instruments searchable, discoverable, and actionable across global capital markets. The AI group develops systems that process and organize structured and unstructured information, uncover signals, produce analytics about financial instruments, and support customer decision-making.
Responsibilities
- Collaborate with colleagues on production machine learning systems and applications.
- Design, experiment with, and evaluate software systems.
- Write, test, and maintain production-quality code.
- Represent Bloomberg at conferences and in open-source communities.
- Demonstrate technical leadership by owning cross-team projects.
- Build libraries and frameworks that support fault-tolerant and testable systems.
- Architect and implement machine learning systems end-to-end for financial-domain applications.
- Contribute to projects involving unified search, question answering, query parsing, financial instrument pricing, and dialogue understanding.
Requirements
- 7+ years of experience working with an object-oriented programming language such as C, C++, Python, or Java.
- A degree in Computer Science, Engineering, Mathematics, or a similar field, or equivalent work experience.
- Understanding of computer science fundamentals, including data structures and algorithms.
- An honest approach to problem-solving and the ability to collaborate with peers, stakeholders, and management.
Benefits
Benefits may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, and vision coverage, short- and long-term disability benefits, a 401(k) match, life insurance, and wellness programs. Compensation also includes a bonus opportunity.