Co-op Software Engineer - AI System & Infrastructure

Huawei Canada has an immediate Co-op opening for an Engineer. About the team: The Intelligent Cloud Infrastructure Lab aims to innovate technologies, algorithms, systems, and platforms for next-generation cloud infrastructure. The lab addresses scalability, performance, and resource utilization challenges in existing cloud services while preparing for future challenges with appropriate technologies and architectures. Additionally, the lab aims to understand industry dynamics and technology trends to create a robust ecosystem. About the job: Understand AI System and Infrastructure technology landscape, and identify scalability/performance issues or challenges of current LLM/multi-modal LLM systems Initiate and charter innovation projects to build or re-architect AI infrastructure platform, and plan milestones accordingly Provide/contribute a scalable and high-performance architecture design or re-design for the infrastructure system that is optimized for AI training and inferencing, which includes but not limited to cluster management and scheduling, LLM model deployment, elastic LLM as well as AI container cold/warm start-up optimization, and so on. Collaborate with internal and external teams to deliver the project or project features that improve our overall system scalability and performance. The target annual compensation (based on 2080 hours per year) ranges from $58,000 to $104,000 depending on education, experience and demonstrated expertise. About the ideal candidate: Bachelors, Master/PhD degree in Computer Science, Computer Engineering Experience in building large scale and high-performance distributed system Experience in Nvidia TensorRT and/or Triton servers. Experience in container virtualization technologies Knowledge & experience in distributed system design & development, including serverless technologies Work experience in one or more of the following technologies: vLLM, Ray, SGLang, Kubernetes, TensorRT-LLM, Pytorch framework, Cuda libraries, GPU technologies Work experience in one or more of the following programming languages: C/C++, Go, Java, Rust, python, C# Have excellent interpersonal and communication skills to collaborate with multiple teams and build strong partnerships effectively Demonstrated success working on software engineering problems that span multiple products

Identify scalability and performance challenges in LLM systems to design high-performance AI infrastructure. Collaborate with teams to implement optimizations for AI training, inferencing, and cluster management.

Requires a degree in Computer Science or Engineering with experience in large-scale distributed systems and GPU technologies. Proficiency in languages like C++, Go, or Python and familiarity with containerization is essential.

Identified from the job description. Confirm important requirements above.

• Distributed Systems
• Nvidia TensorRT
• Triton Servers
• Container Virtualization
• vLLM
• Ray
• SGLang
• Kubernetes
• TensorRT-LLM
• Pytorch
• Cuda
• GPU Technologies
• C/C++
• Go
• Java
• Python

• Software
• Technology
• Engineering
• Science & Research
• Data & Analytics

Minimum education

Bachelor’s degree

Minimum experience

0+ years

Posting language

English

Working hours

40 hours per week