Hardware Validation Engineer (0–5 Years) – Server Platforms

Overview
We are seeking a motivated and hands-on engineer to support post-silicon validation, system bring-up, and hardware debugging in a lab environment. This role involves working closely with server platforms, including CPUs and memory (DIMMs), while leveraging modern tools—including AI-assisted methods—to improve efficiency and troubleshooting.

Key Responsibilities
Perform hardware and software validation testing on server platforms
Build, configure, and bring up systems (CPU, DIMMs, OS/software setup)
Install, swap, and validate CPUs, memory (DIMMs), and system components
Debug and triage hardware/software issues; analyze logs and identify root causes
Support hardware debugging and failure analysis in a lab environment
Utilize Python/Linux tools and AI-assisted methods to improve debug efficiency
Leverage Generative AI tools (e.g., ChatGPT, Copilot, Claude) for log analysis, scripting, and documentation
Explore AI-driven workflows to automate repetitive validation and debug tasks (nice to have)
Maintain lab inventory, systems, and equipment status
Document test procedures, debug findings, and results clearly
Communicate progress, issues, and escalate risks as needed
Manage multiple tasks in a fast-paced environment

Required Qualifications
AAS in Electrical/Computer Engineering or related field (required)
BS/BE/MS in Electrical Engineering (preferred)
0–5 years of experience in hardware validation, lab environments, or related roles
Familiarity with PC/server hardware and system architecture (DDR experience is a plus)
Experience or exposure to Windows and Linux OS installation and configuration
Basic knowledge of Python scripting or automation tools
Understanding of hardware debugging concepts and log analysis
Strong problem-solving skills and willingness to learn

Preferred Skills
Experience with DDR5 and DIMM architecture
Familiarity with BIOS flashing tools (ROM burner or utilities)
Ability to read schematics and identify voltage rails, signals, and registers
Hands-on experience with lab equipment (multimeter, oscilloscope, logic analyzer)
Experience using AI tools to analyze large log datasets or accelerate debug workflows
Exposure to prompt engineering or AI-assisted engineering practices
Curiosity to adopt new tools and continuously improve productivity

Key Competencies
Detail-oriented with strong documentation skills
Ability to follow procedures and work independently
Effective communication and teamwork
Adaptability in a dynamic lab environment