Research Engineer - Software Systems Engineering/LLMs

Huawei; Ontario; On-site; CAD 80,000 - 100,000; Full time

Job summary

Join a forward-thinking company as a Research Engineer, where you will explore the integration of large language models with formal methods to enhance software engineering processes. Collaborate with industry leaders, develop innovative frameworks, and contribute to groundbreaking projects that shape the future of technology. This role offers the opportunity to work on cutting-edge AI advancements, focusing on improving system design and automated testing. If you have a passion for artificial intelligence and a strong background in software engineering, this position is perfect for you!

Qualifications

• PhD or Master's degree in Software Engineering, AI, or related fields.
• Experience with AI/LLMs in software engineering and strong programming skills.

Responsibilities

• Conduct research to apply LLM and AI techniques in software engineering.
• Develop frameworks for integrating LLMs into software engineering workflows.

Skills

Research & Development

Programming Skills

Artificial Intelligence

Natural Language Processing (NLP)

Problem-Solving

Education

PhD in Software Engineering

Master's in Software Engineering

PhD in Artificial Intelligence

Master's in Artificial Intelligence

Tools

LLM Development Tools

Job description

Huawei Canada has an immediate 12-month contract opening for a Research Engineer.

About the team:

The Intelligent Testing Technology Team, currently a part of the Waterloo Research Centre, is at the forefront of integrating large language models (LLMs) with formal methods to advance artificial intelligence. By harnessing LLMs' strengths in natural language processing and generation, this team explores their synergy with the precision of formal verification techniques. As part of this team, you will collaborate with industry leaders on groundbreaking projects and contribute to shaping the future of technology.

About the job:

• Conduct advanced research to explore and apply state-of-the-art LLM and AI techniques to improve 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. This includes applying prompt engineering, retrieval-augmented generation (RAG), self-consistency methods, reflection techniques, search and planning algorithms, and evaluation metrics to enhance system performance and decision-making.

• 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. Communicate research findings through academic publications and industry reports.

• Stay at the forefront of LLM advancements and related AI technologies, identifying opportunities for innovation and contributing to developing next-generation software systems engineering tools and techniques.

About the ideal candidate:

• 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.