Computing Infrastructure Engineer
About this position
Connect computing resources and model workloads to make training and inference environments more stable and efficient.
KAEL focuses on the connection between artificial intelligence, digital technology and industrial applications, and looks forward to you using your professional capabilities to solve practical problems.
you will be responsible
- Build GPU training and inference environments, and maintain container images, dependencies, and deployment configurations.
- Participate in resource scheduling, capacity planning and performance analysis to optimize GPU utilization and task cost.
- Improve model service monitoring, version management, fault recovery and operation documentation.
we look forward to
- Familiar with Linux, Docker and Kubernetes, and capable of infrastructure troubleshooting.
- Understand the basic process of GPU computing, model training, or inference deployment.
- Ability to write automated scripts, analyze resource bottlenecks and verify optimization effects.
Bonus points
Experience with distributed training, inference optimization, MLOps, or infrastructure as code.
Join Us
Please prepare a resume, intended position and representative project introduction. You are also welcome to attach a portfolio or GitHub link. The project description can include your responsibilities, technical solutions and actual results.
Work location, employment methods and salary range will be confirmed in recruitment communications.
Contact the recruitment team