Responsibilities
- Create and build enterprise-level AI structures for handling and examining intricate, multi-faceted financial and alternative data
- Design complete machine learning workflows that manage various data types such as structured market information, unstructured documents, and live data streams
- Build sophisticated natural language processing systems to pull out and verify key measurements from vast numbers of documents, reports, and regulatory files
- Utilize state-of-the-art AI methods, including large language models, computer vision, and deep learning, to address diverse AI applications
- Establish MLOps standards and automated setups for deploying models, tracking performance, and enabling ongoing enhancements across different product groups
- Work with product teams and subject matter experts to convert intricate needs into expandable technical answers
- Offer technical advice and coaching to fellow engineers on AI and machine learning standards and structural choices
- Collaborate with research teams to progress AI uses in financial analysis
- Promote technical quality through code assessments, design records, and information exchange company-wide
- Boost AI engineering team efficiency by employing AI agents to automate activities
