Job Summary
The role focuses on the design, deployment, and maintenance of scalable cloud and GPU infrastructure specifically aimed at facilitating AI and machine learning processes, encompassing training, deployment, and inference. The position also requires the establishment of MLOps and automation workflows, alongside the monitoring and enhancement of the infrastructure’s efficiency and security.
Responsibilities
- Design and implement scalable cloud and GPU infrastructures for AI and machine learning.
- Build and maintain MLOps and automation pipelines.
- Monitor infrastructure performance and optimize resource usage.
- Implement security measures to safeguard cloud environments.
- Troubleshoot and resolve reliability issues in collaboration with engineering teams.
Qualifications
- 2–6 years of experience in AI infrastructure, cloud infrastructure, DevOps, or a related discipline.
- Proficiency with cloud platforms, Docker, Kubernetes, and GPU computing.
- Strong Linux skills and scripting experience.
- Familiarity with CI/CD processes and infrastructure automation techniques.
- Understanding of model deployment, networking, storage solutions, cloud security, and monitoring practices.
- A relevant bachelor’s or master’s degree is preferred.
