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Research Engineer - Software Systems Engineering/LLMs

Huawei Technologies Canada Co., Ltd.

Markham

On-site

CAD 80,000 - 120,000

Full time

30+ days ago

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Job summary

An established industry player is seeking a Research Engineer to join their Intelligent Testing Technology Team. This role involves conducting cutting-edge research to integrate large language models with formal methods, enhancing software engineering processes. The ideal candidate will have a strong academic background in software engineering or AI, with proven research experience in applying LLMs. You'll collaborate with experts to solve complex challenges and contribute to innovative software systems. Join a forward-thinking team that is shaping the future of technology through advanced AI applications.

Qualifications

  • PhD or Master's degree in relevant fields focusing on LLM and AI techniques.
  • Research & development experience in AI/LLMs in software engineering.

Responsibilities

  • Conduct research on LLM and AI techniques to enhance software engineering processes.
  • Develop frameworks for integrating LLMs into software engineering workflows.

Skills

Large Language Models (LLMs)
Artificial Intelligence (AI)
Natural Language Processing (NLP)
Programming Skills
Software Engineering
Requirements Engineering

Education

PhD in Software Engineering
Master's in Software Engineering
Master's in Artificial Intelligence

Tools

LLM Development Tools

Job description

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Research Engineer - Software Systems Engineering/LLMs, Markham

Location:

Markham, Canada

Job Category:

Information Technology

Job Reference:

oeg3vgs4

Job Views:
Posted:
Expiry Date:

06.05.2025

Job Description:

Huawei Canada has an immediate permanent 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:

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. Stay at the forefront of LLM advancements and related AI technologies, identifying opportunities for innovation and contributing to the development of 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.

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