Co-op Engineer- Distributed Agent System
About The Position
Our team has an immediate 8-16-month Co-op opening for an Engineer. The Distributed Scheduling and Data Engine Lab is Huawei Cloud's technical innovation center in Canada, established in 2014. The lab focuses on researching and developing advanced cloud technologies, supporting the productization and iterative optimization of its technical achievements. Current research areas include cloud native databases, intelligent SQL engine, LLM/Agent infrastructure and LLM/Agent Evaluation Technology. The lab fosters a robust technical environment, allowing collaboration with industry experts to create a highly competitive cloud platform. In this role, you will work with architects and engineers to develop proof-of-concept systems and product components for AI-native cloud infrastructure. You will investigate and design data structures and algorithms for distributed resource scheduling, capacity optimization, and workload placement on modern cloud hardware. You will also continuously enhance the data system used for public cloud capacity management and scheduling.
Requirements
- Bachelor’s, Master’s, or Ph.D. studies in Computer Science, Computer Engineering, Applied Mathematics, Physics, or a related field.
- High proficiency in Go or Rust, with the ability to write clean, maintainable code from scratch.
- Strong understanding of algorithms, data structures, object-oriented design, and operating systems.
- Understanding of distributed databases, storage systems, file systems, memory allocation, or cache systems.
- Strong analytical and problem-solving skills.
- Self-motivation, initiative, and the ability to learn quickly.
- Ability to clearly explain technical concepts, design tradeoffs, and implementation challenges.
Nice To Haves
- Experience with scheduling algorithms, Linux system-level development, or distributed systems is an asset.
Responsibilities
- Work with architects and engineers to develop proof-of-concept systems and product components for AI-native cloud infrastructure.
- Investigate and design data structures and algorithms for distributed resource scheduling, capacity optimization, and workload placement on modern cloud hardware.
- Continuously enhance data system used for public cloud capacity management and scheduling.
Benefits
- Fair, inclusive, and accessible recruitment process
- Accommodation during any stage of the hiring process
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What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
Ph.D. or professional degree
