Silicon Validation Engineer
NVIDIAJob Title
Silicon Validation Engineer
Role Summary
Join NVIDIA's Silicon Co-design Group (HW ArchDev Methodology) to define system-level validation strategies, automation frameworks, and telemetry for next-generation GPUs and AI accelerators. The team spans architecture, silicon bring-up, and production.
The role focuses on creating scalable validation workflows, driving silicon bring-up and root-cause debug, and deploying telemetry and automation across products and teams.
Experience Level
Mid-level (Level - Mid-Career). The posting requests 2+ years of relevant experience in silicon bring-up, ASIC validation, or system-level debug.
Responsibilities
Core responsibilities include designing validation methods, building automation, and supporting silicon bring-up and debug.
- Design system-level validation strategies for complex architectures, corners, PVT, timing, and feature interactions.
- Develop AI-assisted and data-driven validation workflows to improve coverage and debug turnaround.
- Profile real workloads (training, inference, HPC, video, and emerging applications).
- Deploy automation and telemetry pipelines that scale across products and teams.
- Lead silicon bring-up and root-cause debug using reusable, high-leverage methods.
Requirements
Must-have technical skills and experience for immediate contribution; nice-to-have items indicate stronger candidates.
- Must-have: 2+ years in silicon bring-up, ASIC validation, or system-level debug.
- Must-have: Practical grounding in PVT, timing (STA), signal integrity, power, and high-speed I/O (PCIe, chip-to-chip).
- Must-have: Understanding of firmware/driver ↔ hardware interaction and experience debugging across software and silicon layers.
- Must-have: Experience or strong interest in data-driven workflows, telemetry, and AI/LLM-assisted development for validation.
- Must-have: Ability to work collaboratively across architecture, firmware, validation, and manufacturing teams.
- Nice-to-have: Applied AI/ML or LLMs to validation, debug automation, or workload analysis in production or research contexts.
- Nice-to-have: Built reusable infrastructure such as pipelines, observability systems, or debug tools used by other teams.
- Nice-to-have: Artifacts demonstrating methods and thinking (postmortems, test methods, tools, papers, dashboards).
Education Requirements
BS or MS in Electrical Engineering, Computer Engineering, Computer Science, or related technical field is listed; the posting also allows "equivalent experience."
About the Company
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
