2 months ago
Base Salary
$200k - $288k/yr
Responsibilities
- Design and build a multi-cloud capacity platform for CPU and GPU allocation, procurement, reservation lifecycle, and utilization.
- Own a canonical data layer that reconciles demand forecasts, provider supply signals, commitments, and fleet utilization.
- Integrate cloud-provider relationships and provisioning workflows into capacity planning and procurement systems.
- Build planning and allocation systems that identify hardware requirements and surface supply risks with real-time fleet and reservation visibility.
- Instrument CPU and GPU workload utilization, establish price/performance baselines, and recover stranded capacity through right-sized commitments.
- Evaluate new CPU and GPU generations and implement cross-family fallback and migration flexibility.
- Partner with core services, warehouse, AI/ML, and finance teams to forecast and procure capacity for launches and workloads.
- Maintain high availability, reliability, and performance through on-call rotations and incident management.
Requirements
- 7+ years of industry experience designing, building, and supporting large-scale production systems.
- Hands-on experience working with cloud providers to provision compute clusters and cloud services for CPU and/or GPU fleets.
- Experience with capacity planning, procurement, resource management, or efficiency work in large private or public clouds.
- Deep systems and architectural analysis experience across performance, availability, and efficiency of CPU and GPU fleets.
- Proficiency in Go, Python, or Java.
- Strong production troubleshooting, problem-solving, communication, and collaboration skills.
- BS or MS in Computer Science, Engineering, or a related field.
- Experience with observability infrastructure such as OpenTelemetry or Prometheus is preferred.
- Familiarity with accelerator/GPU fleets, hardware price/performance analysis, or Kubernetes-based compute at scale is preferred.
- Background in modeling, forecasting, cloud spend optimization, or LLMs is preferred.
Tech Stack
About Snowflake
Snowflake builds a cloud-native data platform used by enterprises to store, integrate, share, and analyze data across AWS, Azure, and Google Cloud. Its core products span data warehousing, data lakes, data engineering, and governed data sharing, sold via consumption-based subscriptions. Founded in 2012 and publicly traded on the NYSE (SNOW) following a 2020 IPO, Snowflake supports analytics and data application workloads across industries.