System Validation Engineer, AI Hardware

Tesla Tesla · Auto · Palo Alto, CA · Tesla AI

Tesla is seeking a System Validation Engineer to build comprehensive test frameworks and validation infrastructure for their AI datacenter systems, including servers, racks, networking, and storage. The role involves developing automated test suites, stress-testing hardware under production AI workloads, and ensuring performance, reliability, and efficiency.

What you'd actually do

  1. Design and implement automated validation frameworks for AI datacenter systems—servers, racks, networking, and storage—to ensure production readiness
  2. Develop and execute test suites to validate hardware functionality, performance benchmarks, thermal characteristics, and long-term reliability under production AI workloads
  3. Build performance benchmarking and diagnostic tools to measure compute throughput, network bandwidth, storage I/O, power consumption, and thermal efficiency
  4. Automate data collection and analysis to track validation results, identify trends, and generate actionable insights for hardware design improvements
  5. Develop sw deployment, orchestration and testing pipelines with tools like Docker and configuration testing (e.g., Ansible)

Skills

Required

  • Python for test automation and data analysis
  • design and implement automated test frameworks
  • burn-in testing
  • stress testing
  • performance benchmarking
  • datacenter systems validation
  • servers
  • networking equipment
  • storage systems
  • power/thermal infrastructure
  • distributed computing
  • containerization
  • orchestration
  • CI/CD tools
  • debugging skills across hardware and software domains
  • analyze complex data sets

Nice to have

  • AI/ML infrastructure or GPU cluster validation
  • statistical analysis
  • data visualization (Grafana, Kibana, Prometheus)
  • performance modeling
  • Linux system administration
  • scripting (Bash, shell)
  • test frameworks (pytest, unittest)
  • lab test equipment
  • HPC technologies (Ethernet, InfiniBand, RDMA, PCIe, NVMe, or high-speed interconnects)

What the JD emphasized

  • production readiness
  • production AI workloads
  • performance
  • reliability
  • efficiency