Technical Leader - AI System & Infrastructure

Huawei Technologies Canada Co., Ltd.; Vancouver; On-site; CAD 160,000 - 220,000; Full time

Job summary

An innovative firm is seeking an Engineer to join its Intelligent Cloud Infrastructure Lab. This role focuses on enhancing AI systems and infrastructure, tackling scalability and performance challenges. The ideal candidate will possess a Master's or PhD in Computer Science or Engineering, with a strong background in distributed systems and technical leadership. You'll collaborate with diverse teams to drive projects that optimize AI infrastructure, ensuring high performance and scalability. If you're passionate about advancing cloud technologies and thrive in a dynamic environment, this opportunity is perfect for you.

Qualifications

• Master/PhD in Computer Science or Engineering required.
• Experience in large scale distributed systems and AI infrastructure.

Responsibilities

• Identify scalability issues in AI systems and initiate innovation projects.
• Design high-performance architecture for AI training and inferencing.

Skills

Technical Leadership

Distributed Systems

Interpersonal Skills

Communication Skills

AI Infrastructure

Education

Master's Degree in Computer Science

PhD in Computer Engineering

Tools

Nvidia TensorRT

Triton Servers

Kubernetes

Pytorch Framework

Cuda Libraries

Job description

Huawei Canadahas an immediate permanent opening foran 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 base salary for this position ranges from $160,000 to $220,000 depending on education, experience and demonstrated expertise

About the ideal candidate:

• Master/PhD degree in Computer Science, Computer Engineering

• Technical Leadership Experience

• 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