Automation Engineer-GPU Validation

Description: Top Mandatory Skills

GPU platform validation: GPU driver installation, GPU enumeration, firmware compatibility and PCIe validation (topology and link checks) on data center GPUs.

Workload and system validation: Functional, regression, stress and workload testing, including thermal, power, GPU utilization and memory validation.

Server platform and BIOS validation: Bringing up and validating data center servers (Dell PowerEdge / Supermicro / HPE), including BIOS setup and validation.

Firmware, BMC and driver validation: Validating BMC, firmware and drivers, including firmware version pairing and upgrade/downgrade paths.

Hardware troubleshooting and root cause analysis: In-depth debugging of hardware, firmware and driver failures during bring-up and validation, such as boot/POST hangs, reset failures and enumeration issues.

AI/HPC workload validation and characterization: Running and analyzing AI/HPC workloads, and measuring performance and stability.

Linux and CLI skills: Hands-on with Ubuntu and RHEL, including OS installation and imaging, driver setup and command-line tools for system and GPU diagnostics.

Log analysis and automation: Analyzing system, BMC and driver logs, running Python scripts and reviewing automation results.

Availability: Flexibility to work weekends and extended hours when needed during critical release validation phases.

Nice-to-Have Secondary Skills

Test planning: Writing test cases, test plans and coverage matrices for hardware, firmware, IP blocks and drivers.

Multi-GPU and networking validation: Running collective communication benchmarks across multiple GPUs and nodes and validating high-speed NICs and RDMA.

Virtualization: VMware ESXi, GPU passthrough and GPU partitioning.

Scripting: Basic Python or shell scripting to automate tests and parse logs.

Tools: Experience with Jira for test management and defect tracking.