Artificial Intelligence Researcher
7 days ago
About the Role
We are seeking a talented Research Engineer to join our team at Huawei. As a Research Engineer, you will play a critical role in developing and applying cutting-edge Large Language Models (LLMs) and Artificial Intelligence (AI) techniques to improve software engineering processes.
Key Responsibilities:
- Conduct advanced research to explore and apply state-of-the-art LLM and AI techniques to enhance software engineering processes, including requirements analysis, system design, modelling, and automated software testing.
- Develop novel frameworks and methodologies for integrating LLMs into software engineering workflows, leveraging techniques such as prompt engineering, retrieval-augmented generation (RAG), self-consistency methods, reflection techniques, search and planning algorithms, and evaluation metrics.
- Design and implement techniques that combine symbolic reasoning with generative AI models, aiming to bridge the gap between data-driven and logic-based approaches to problem-solving in software systems.
- Collaborate with cross-functional teams of researchers, engineers, and product experts to integrate AI-driven solutions into real-world software systems engineering challenges, communicating research findings through academic publications and industry reports.
What You'll Bring
- A PhD or Master's degree in Software Engineering, Requirements Engineering, Artificial Intelligence, Natural Language Processing (NLP), or closely related fields, with a focus on the application of Large Language Models and AI techniques.
- Research & development experience in the application of AI/LLMs in the software engineering domain, with a solid understanding of both theoretical foundations and practical implementations; Strong programming skills and experience in LLM development tools.
- Proven ability to address complex challenges in AI/LLM applications, particularly in integrating AI-driven insights into software engineering tasks such as requirement specification, system design, and quality assurance.
- Demonstrated ability to work effectively in interdisciplinary teams, with strong communication skills to convey complex technical concepts to non-expert stakeholders and present findings at conferences or workshops.
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