Machine Learning Engineer
Rasa
Python
VP, Data Science – GenAI
skillventory - A Leading Talent Research Firm
full-time
Posted on:
Origin: • 🇺🇸 United States
Visit company websiteJob Level
Lead
Tech Stack
Python
About the role
- Conceive, build and deliver first-of-a-kind knowledge-based GenAI applications for investment professionals.
- Develop a Large Language Model (LLM)-first knowledge stack to process analyst reports, earnings notes, spreadsheet models, prospectuses, loan indentures, news reports, and regulatory filings.
- Support deployment of personalized assistants for analysts and portfolio managers to summarize documents, answer passage questions, extract terms, compare information across time/deals, consolidate and restate agreements, identify trends, monitor changes, generate scenarios, analyze factors, and produce reports.
- Combine symbolic, logic-based representations with informal, text-based domain content to solve business problems.
- Collaborate with cross-functional teams to improve assistants over time and deploy production-grade GenAI systems.
Requirements
- PhD or Master's in AI/ML, Computer Science or Finance (with a background in Machine learning).
- 5+ years of industrial experience.
- Understanding of how innovative LLMs can be induced to use explicitly supplied structured and unstructured information, their implicit world knowledge and their slow-thinking abilities to solve domain-specific problems.
- Grasp of logic- and ML-based AI techniques for knowledge extraction, representation and reasoning.
- Expertise in combining symbolic, logic-based representations (e.g. knowledge graphs, ontologies) with informal, text-based domain content to solve business problems.
- Understanding of how to deliver into production GenAI applications that can reliably process information in open-ended settings.
- Track record of managing the "exploration vs exploitation" tradeoff to deliver innovative solutions for first-of-a-kind problems.
- Deep expertise in Python, data-centric AI (ML) techniques, particularly as applied to text, tables, documents.
- Excellent knowledge of standard tools of the trade for machine learning engineers.
- Excellent collaboration skills and experience working as part of an applied technical team.
