Co-op Software Engineer - AI System & Infrastructure
- Vancouver, BC, Canada
The target annual compensation (based on 2080 hours per year) ranges from $58,000 to $104,000 depending on education, experience and demonstrated expertise. · Internship
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Job details
- Pay
- The target annual compensation (based on 2080 hours per year) ranges from $58,000 to $104,000 depending on education, experience and demonstrated expertise.
- Job type
- Internship
- Posting language
- English
- Posted
Original job description
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.
Job requirements
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
More about this job
Responsibilities
The role involves understanding the AI System and Infrastructure technology landscape and identifying scalability and performance challenges. The engineer will initiate innovation projects to build or re-architect AI infrastructure platforms and collaborate with teams to improve system scalability and performance.
Requirements
The ideal candidate should have a Bachelor's, Master's, or PhD degree in Computer Science or Computer Engineering and experience in building large-scale distributed systems. Familiarity with technologies such as Nvidia TensorRT, container virtualization, and programming languages like C/C++, Python, and Java is also required.
Skills
- Distributed System Design
- Container Virtualization
- Nvidia TensorRT
- Triton Servers
- Serverless Technologies
- Kubernetes
- Pytorch Framework
- Cuda Libraries
- GPU Technologies
- C/C++
- Go
- Java
- Rust
- Python
- C#
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Engineering
- Software
- Data & Analytics
- Science & Research
Keywords
- AI
- Infrastructure
- Cloud
- Scalability
- Performance
- Resource Utilization
- Distributed Systems
- Nvidia TensorRT
- Triton Servers
- Container Virtualization
- Serverless Technologies
- Kubernetes
- Pytorch
- Cuda
- GPU
- C/C++
- Go
- Java
- Rust
- Python
- C#
- LLM
- Multi-modal LLM
- Cluster Management
- Scheduling
- Model Deployment
- Elastic LLM
- AI Container Optimization
- Collaboration
- Engineering