Information Retrieval Algorithm Engineer

# Research Engineer - Large Language Models & Reinforcement Learning

## Team Introduction
Huawei Amsterdam Research Center is at the forefront of innovation in artificial intelligence and machine learning. The team is dedicated to developing advanced technologies that transform how people interact with information and enhance productivity across various sectors.

## Position Overview
We are seeking a highly skilled and motivated Research Engineer to join our team, focusing on building advanced AI systems based on Large Language Models (LLMs) enhanced with Reinforcement Learning (RL). The ideal candidate has hands-on experience applying RL techniques to train and align large language models, with particular emphasis on agentic applications such as deep research and automated code generation.

You will be responsible for designing and developing advanced LLM-powered Multi-Agent systems trained and aligned using Reinforcement Learning, targeting complex agentic scenarios including deep research and automated code generation. You will work closely with our team of researchers, data scientists, and engineers to advance the capabilities of LLM-based agents.

## Key Responsibilities

• Design and develop LLM-based multi-agent AI systems, applying Reinforcement Learning (e.g., RLHF, RLAIF, PPO, GRPO) to train, align, and optimize agents for complex agentic tasks
• Utilize RL training frameworks (e.g., verl, OpenRLHF, TRL) and agent orchestration frameworks (e.g., LangChain, LlamaIndex) to build, train, test, and deploy autonomous AI agents at scale
• Research and implement RL-based training pipelines and reward modeling strategies to improve LLM agent performance on long-horizon tasks
• Develop and integrate advanced knowledge management and Retrieval-Augmented Generation (RAG) systems to provide AI agents with accurate and timely information
• Stay current with and contribute to the latest research in Large Language Models, Reinforcement Learning for LLMs, agentic AI systems, and domain-specific applications
• Collaborate with cross-functional teams to integrate the AI solutions you develop into existing products and services
• Evaluate and benchmark the performance of AI Agent systems and perform iterative optimization