Join CFM, a global quantitative and systematic asset management firm, as an intern in the Data Referential Chatbot project. You will work on expanding an AI assistant designed to efficiently retrieve information from our data using natural language processing. Your responsibilities will include industrializing the existing solution, benchmarking LLM models, augmenting the scope, integrating the assistant into the existing data-catalog, exploring new features, and documenting the process. Ideal candidates should have a strong background in computer science or data science, experience in programming Python and SQL, and knowledge of AI/LLMs.
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Industrialization of the POC: Develop and deploy the existing Chatbot AI Assistant solution ensuring scalability and reliability.
Benchmarking LLM Models: Conduct a comprehensive evaluation and benchmarking of different LLMs to identify the most effective model for the assistant's use case.
Scope Augmentation: Expand the database, integrating additional data sources that enhance the AI Assistant's capabilities.
ABOUT CFM
Founded in 1991, we are a global quantitative and systematic asset management firm applying a scientific approach to finance to develop alternative investment strategies that create value for our clients.
We value innovation, dedication, collaboration, and the ability to make an impact. Together, we create a stimulating environment for talented and passionate experts in research, technology, and business to explore new ideas and challenge existing assumptions.
Internship Overview :
This internship builds upon an initial project aimed at developing an AI assistant designed to efficiently retrieve information from our data using natural
language processing. Initially, our efforts concentrated on data stored in SQL databases, encompassing only a few dozen tables.
We now aim to expand this project, requiring a system capable of accessing hundreds or even thousands of tables while maintaining speed and highquality
responses.
Additionally, we seek to integrate a wide array of data sources, particularly datasets in parquet format.
Another objective is to enhance dataset documentation capabilities and enable the automatic creation of notebook reports for exploratory data analysis on
these parquet datasets.
The successful candidate will collaborate with cross-functional teams to transform the assistant into a powerful tool that boosts operational efficiency.
Key Responsibilities:
Desired Skills and Qualifications:
Strong background in computer science, data science, or related fields.
Experience in programming Python, SQL.
Experience with AI / LLMs.
Problem-solving skills and an attention to detail.
Knowledge of cloud architecture, including AWS tools like Lambda, S3, and SageMaker is a plus.
Effective communication and collaboration abilities across multi-disciplinary teams.
EQUAL OPPORTUNITIES STATEMENT
We are continuously striving to be an equal opportunity employer and we prohibit any discrimination based on sex, disability, origin, sexual orientation, gender identity, age, race, or religion. We believe that our diversity, breadth of experience, and multiple points of view are among the leading factors in our success.
CFM is a signatory of the Women Empowerment Principles.
Follow us on Twitter or LinkedIn or visit our website to find out more about CFM.
Profile description:
Strong background in computer science, data science, or related fields.
Experience in programming Python, SQL.
Experience with AI / LLMs.
Problem-solving skills and an attention to detail.
Knowledge of cloud architecture, including AWS tools like Lambda, S3, and SageMaker is a plus.
Effective communication and collaboration abilities across multi-disciplinary teams.
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