Internship - Research Engineer - Benchmarking and optimization of tool usage by language models. (in collaboration with MICS CentraleSupelec)
Core
Research internship focusing on benchmarking and optimizing tool usage by language models within a black-box environment (LLM + MCP servers) to maximize tool success rates.
Role type
Research Engineer Intern
Builds
MCP server architectures and optimization strategies for AI agents
Domain
Artificial Intelligence, Large Language Models, Model Context Protocol (MCP)
Deliverable
production ML models
Required skills
software development, independent work, research methodology
Preferred skills
TypeScript, React, Nest.js, Reinforcement Learning, Fine-tuning, AI/ML research
Technologies
LLM, MCP servers, Reinforcement Learning
Responsibilities
Research parameters impacting tool success rates in black-box LLM environments, propose new MCP server architectures (e.g., adding SF or RL loops), test results on Alpic infrastructure
Seniority
Intern
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