You will design, automate, and manage the lifecycle of high-performance customer compute environments, including Kubernetes and Slurm clusters. The role involves operating the NVIDIA GPU stack, configuring data-center networking, and building robust monitoring and recovery systems.
You will design, build, and operate public and private network infrastructure to support high-performance AI compute clusters and serverless platforms. The role involves managing BGP routing, IP address space, and network observability while leveraging automation to ensure reliability and performance.
Own the reliability, security, and safety of generative media model APIs to ensure high availability and performance. Build monitoring systems to detect ML-specific failures and lead incident response for model API outages.
Build and maintain software and tooling to manage a large fleet of GPU servers, focusing on provisioning, health monitoring, and recovery. Optimize Linux systems and storage for AI workloads while implementing OS-level security and compliance.
Own and operate Kubernetes infrastructure, including cluster lifecycle, networking, and multi-tenant isolation. Build and maintain CI/CD pipelines while leveraging AI to automate production issue resolution and improve system reliability.
Build and maintain software and tooling to manage a large fleet of GPU servers, focusing on provisioning, health monitoring, and recovery. Optimize Linux systems for AI workloads and implement OS-level security and storage management.
Build and evolve a core Python/Rust platform focusing on request routing, AI workload orchestration, and GPU autoscaling. Design systems to handle 100x traffic growth while maintaining low latency and high reliability.
Own and operate Kubernetes infrastructure, including cluster lifecycle, networking, and multi-tenant isolation. Build and maintain CI/CD pipelines while leveraging AI to automate production issue resolution and improve system reliability.
Provide advanced technical support to customers and internal teams by resolving API, UI, and integration issues. Collaborate with engineering to document bugs, improve platform reliability, and maintain technical documentation.
Build and operate the data infrastructure and ETL pipelines to track cost, margin, and performance across production systems and vendor APIs. Partner with infrastructure and product teams to define data contracts and implement low-latency analytical write paths.
