Position: Senior Data Scientist
Company: Grid Dynamics
Experience required: 5y
English level: upper

**Project description**
We are going to build a conversational question-answering system for the internal knowledge base (documents) using the latest developments in Large Language Models (LLMs).
The client is looking to improve financial advisors' productivity by providing them with convenient tools to access company knowledge.
They would like to evaluate the potential of conversational AI powered by a large language model for this mission.
Conversational AI would support natural language dialog on top of the “knowledge base”: articles, documents, policies, FAQs, and similar sources of information.
Conversational AI should support semantic search over the knowledge base and question-answering based on relevant documents.

**Client description**
A big US corporation in the area of wealth management located in Florida.

**Details on the tech stack**
Python, Open AI API, vector search engines.

**Min requirements**
- Experience with Python, Deep Learning (PyTorch/TensorFlow), NLP, Transformers
- Experience with one the cloud providers such as AWS/GCP/Azure

**Nice to have requirements**
- Basic understanding of LLM such as ChatGPT, and how they can be applied to different problems using prompt engineering
- Experience with Vector Search
- Experience with Conversational AI

**Team**
~4 engineers for the PoC phase with scaling after success

**Tasks**
- Identify, collect, and analyze a sample knowledge base
- Develop a conversational AI POC based on this knowledge base
- Integrate and evaluate OpenAI conversational models
- Integrate a simple conversational UI to interact with a conversational AI agent