Research Engineer - Formal Methods/LLMs

Huawei Technologies Canada Co., Ltd.; Markham; On-site; CAD 80,000 - 110,000; Full time

Job summary

A leading technology firm in York Region is seeking a Research Engineer for a 12-month contract. The ideal candidate will have a Ph.D. in Computer Science or related fields and experience in symbolic AI and formal methods. Responsibilities include engaging in innovative research on neuro-symbolic systems and collaborating on publications. This role offers a unique opportunity to advance the field of AI through cutting-edge projects.

Qualifications

• Ph.D. in a relevant field preferred, focusing on symbolic techniques.
• Experience in developing symbolic computation tools.
• Understanding of programming language theory and symbolic verification.

Responsibilities

• Engage in research on neuro-symbolic systems leveraging symbolic AI.
• Implement and validate innovative NSS designs.
• Collaborate on research publications.

Skills

Neuro-symbolic systems

Symbolic AI

Formal methods

Programming language tools

Compilers

Model checkers

Theorem provers

Functional programming (Haskell)

Education

Ph.D. in Computer Science, Software Engineering, or Mathematics

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

• Engage in research projects focused on neuro-symbolic systems (NSSs) that leverage symbolic AI and formal methods to enhance and refine LLM outputs, ensuring the generation of acceptable symbolic results
• Implement innovative NSS designs and validate their intended properties
• Collaborate on research publications to disseminate findings

About the ideal candidate

• A Ph.D. in Computer Science, Software Engineering, Mathematics, or a related field, with a preference for candidates specializing in symbolic techniques, particularly in formal methods tools
• Proven experience in developing symbolic computation tools, such as programming language tools, compilers, model checkers, theorem provers, or similar applications. Familiarity with functional programming languages, especially Haskell, is an asset
• A solid understanding of programming language theory, logic, and symbolic verification is an asset
• A strong interest in the integration of LLMs with symbolic tools
• Knowledge of Category Theory is an asset