Senior Cluster Site Reliability Engineer

The Voleon Group is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. They are seeking a Senior Cluster Site Reliability Engineer to scale their research compute cluster, ensuring high uptime and reliability while supporting both on-prem and cloud infrastructure.

Responsibilities:

• Be a first responder in the event of cluster outages or issues. Triage and resolve urgent issues as they arise
• Ensure a high degree of cluster uptime (measured in multiple nines), and define + track SLAs to quantify reliability
• Diagnose systemic/recurring patterns of problems, and engineer precision solutions to them in collaboration with engineering teams
• Develop robust metrics and observability for cluster health and use those metrics to inform your work. Build out custom observability mechanisms when off-the-shelf ones won't do
• Help software and research teams design policies around fair cluster usage, and help develop enforcement mechanisms for said policies
• Assist in forecasting cluster growth, and help select appropriate scale-up strategies. Help optimize operations across dimensions of cost and usability

Requirements:

• 5+ years of experience in SRE or DevOps roles, preferably working as a senior engineer or tech lead
• Knowledge of HPC/batch compute frameworks (Slurm, Kueue, AWS/GCP Batch) and/or machine learning training systems (Kubeflow, MLflow, Horovod)
• Ability to develop scripts and utilities of moderate complexity in a common scripting language (Python, Ruby, etc.)
• Familiarity with infrastructure-as-code and configuration management tools (Terraform, Ansible)
• Experience with cloud infrastructure (AWS or GCP)
• Familiarity designing and implementing modern observability stacks (Prometheus, Grafana, Loki, ELK, OpenTelemetry)
• Experience with distributed storage technologies (Lustre, Ceph, S3)
• Embodies a 'system engineer' rather than 'system administrator' mindset, thinking systematically and leveraging automation
• Bachelor degree in computer science
• Hands-on experience with HPC frameworks (Slurm, Grid Engine) and Kubernetes-based job orchestrators (Airflow, Kueue, Kubeflow Pipelines), along with other distributed computing frameworks (Ray, Modin, Dask, Spark)
• Familiarity with ML frameworks (PyTorch/Tensorflow, JAX, Horovod, DeepSpeed)
• Familiarity with hybrid/on-prem environments
• Experience with containerization (Docker, Podman, Singularity), particularly for HPC/batch compute environments
• Experience with HPC networking (InfiniBand, RDMA)
• Solid security/IAM foundations (Identity management systems, AWS/GCP IAM, Zero Trust)