Site Reliability Engineer (HPC)

Reliability & Availability: Ensure uptime, resiliency, and fault tolerance of HPC clusters powering MAI model training and inference. Observability: Design and maintain monitoring, alerting, and logging systems to provide real-time visibility into all aspects of HPC systems including GPU, clusters, storage and networking. Automation & Tooling: Build automation for deployments, incident response, scaling, and failover in CPU+GPU environments. Incident Management: Lead on-call rotations, troubleshoot production issues, conduct blameless postmortems, and drive continuous improvements. Security & Compliance: Ensure data privacy, compliance, and secure operations across model training and serving environments. Collaboration: Partner with ML engineers and platform teams to improve developer experience and accelerate research-to-production workflows. Master's Degree in Computer Science, Information Technology, or related field AND 2+ years technical experience in Site Reliability Engineering, DevOps, or Infrastructure Engineering OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 4+ years technical experience in Site Reliability Engineering, DevOps, or Infrastructure Engineering OR equivalent experience Strong proficiency in Kubernetes, Docker, and container orchestration. Knowledge of CI/CD pipelines for Inference and ML model deployment. Hands-on experience with public cloud platforms like Azure/AWS/GCP and infrastructure-as-code. Expertise in monitoring & observability tools (Grafana, Datadog, OpenTelemetry, etc.). Strong programming/scripting skills in Python, Go, or Bash. Solid knowledge of distributed systems, networking, and storage. Experience running large-scale GPU clusters for ML/AI workloads (preferred). Familiarity with ML training/inference pipelines. Experience with high-performance computing (HPC) and workload schedulers ( Kubernetes operators). Background in capacity planning & cost optimization for GPU-heavy environments. Work on cutting-edge infrastructure that powers the future of Generative AI. Collaborate with world-class researchers and engineers. Impact millions of users through reliable and responsible AI deployments. Competitive compensation, equity options, and comprehensive benefits.