Senior AI Solutions Architect - Semiconductors
NVIDIAJob Title
Senior AI Solutions Architect - Semiconductors
Role Summary
Senior Solutions Architect supporting semiconductor customers (EDA vendors, chip designers, equipment OEMs, and fabs). Serve as a technical advisor to embed NVIDIA accelerated computing, computational lithography, and AI into design, verification, lithography, and manufacturing workflows.
Work includes customer engagement, performance analysis, solution design, and cross-functional collaboration with engineering, product, and research teams.
Experience Level
Senior-level. The role expects 4+ years of relevant experience in semiconductor design, EDA, or semiconductor manufacturing and/or AI/ML applied to these domains.
Responsibilities
Primary responsibilities include technical customer engagement, solution acceleration, and ecosystem enablement.
- Partner with Business Development, Sales, and Developer Relations to drive semiconductor account success.
- Engage directly with EDA/CAD developers and customer design and manufacturing teams in customer-facing settings.
- Help developers GPU-accelerate and scale EDA workflows (place-and-route, simulation, timing/power analysis, DRC/LVS, verification) and computational lithography.
- Apply ML/DL to defect detection, inspection/metrology, yield optimization, and process control.
- Analyze application architectures to identify performance and scaling opportunities.
- Provide feedback to engineering and product teams and deliver technical demonstrations, trainings, and hackathons.
Requirements
Must-have technical skills and experience; nice-to-have items listed separately.
- 4+ years in semiconductor design, EDA, semiconductor manufacturing, or AI/ML applied to these domains.
- Familiarity with EDA flows and tools (e.g., Cadence, Synopsys, Siemens EDA) or computational lithography/TCAD/inspection systems.
- Proficiency in programming with Python and C/C++; experience GPU-accelerating compute-intensive workloads.
- Experience with major AI frameworks (PyTorch, TensorFlow) for vision or manufacturing use cases.
- Knowledge of accelerated computing platforms, GPU-based distributed systems, and HPC clusters.
- Experience with containers, numerical libraries, modular software design, and version control (GitHub).
- Strong written and verbal communication skills and customer-facing collaboration experience.
- Nice-to-have: CUDA/CUDA-X libraries, NVIDIA cuLitho or GPU-accelerated EDA flows, Kubernetes/distributed training, PCIe accelerators (GPUs, FPGAs), and direct fab inspection/metrology or yield optimization experience.
Education Requirements
MS or PhD in Electrical or Computer Engineering, Materials Science, Applied Physics, Computational Science, or a related technical field — or equivalent practical 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.
