Senior Machine Learning Engineer - Artificial Intelligence
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
Communication @ 6
Data Structures @ 4
Deep Learning @ 4
LLM
Machine Learning @ 4
Mathematics @ 4
Statistics @ 4
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 450 AI practitioners building products and features that require novel innovations. The team develops 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. Its AI systems process and organize structured and unstructured information, uncover signals, produce analytics about financial instruments across asset classes, and deliver insights to clients.
Responsibilities
- Collaborate with colleagues on production systems.
- Write, test, and maintain production-quality code.
- Design, train, experiment with, and evaluate machine learning models, algorithms, and solutions.
- Demonstrate technical leadership by owning cross-team projects.
- Stay current with the latest machine learning research and incorporate new findings into 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 at leading academic venues.
Requirements
- Practical experience solving machine learning problems and applying machine learning techniques.
- Ph.D. in machine learning, statistics, or a relevant field; or an MSc in computer science, machine learning, mathematics, statistics, engineering, or a related field with 2+ years of relevant work experience.
- Experience with machine learning and deep learning frameworks.
- Understanding of computer science fundamentals, including data structures and algorithms.
- A data-oriented approach to problem-solving.
- Excellent communication skills and the ability to collaborate with engineering peers and non-engineering stakeholders.
- A track record of authoring publications in top conferences and journals is a strong plus.
Benefits
Benefits and total rewards may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, vision, short- and long-term disability benefits, a 401(k) match, life insurance, and wellness programs. Benefits are not provided directly to contingent workers, contractors, or interns.