Research Computing Cloud Engineer
Position Overview
We are seeking a highly skilled Cloud Engineer to help build the next generation of Stanford’s research computing environment. This role will work on multiple projects and you will design and implement scalable, secure cloud architectures that may include high-performance computing (HPC) and cutting-edge AI/ML workloads.
Key Responsibilities
- Research, HPC & AI Infrastructure: Architect cloud-native and hybrid solutions for compute intensive workloads, such as AI training and genomics.
- Cloud Bursting & Integration: Develop automated pipelines to "burst" workloads from on-premises HPC clusters to the cloud (AWS/GCP/Azure).
- Technical Consulting, Implementation, and Maintenance: In collaboration with other campus, and cloud vendor based, experts provide guidance on the use of cloud technologies to support research - including cloud architecture, cost optimization, and performance tuning.
Qualifications
Education & Experience
- Bachelor's degree and eight years of relevant experience or a combination of education and relevant experience.
- Degree in Computer Science, Engineering, or equivalent professional experience in a large-scale research computing environment or similar is preferred.
Qualifications
- Cloud Expertise: Advanced experience with major cloud platforms: GCP, AWS or Azure
- Compute Specialization: Hands-on experience with HPC job schedulers (e.g., Slurm) and/or GPU computing (CUDA, NVIDIA software stacks). Experience with cloud-bursting and/or integration of on-premise systems with cloud environments is a plus.
- DevOps & Automation: Proficiency in Infrastructure as Code (Terraform, Ansible) and containerization (Docker, Kubernetes).
- Data Movement: Experience with orchestration of data movement between on premise and cloud environments. Experience with Globus a plus.
- Security & Compliance: Understanding of data privacy frameworks (HIPAA, CMMC) within a research context.
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