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NVIDIA AI

18 Nvidia Ai Jobs Hiring Near You

NVIDIA AI

Senior Robotics Research Scientist

Seattle, WA · On-site

$112K - $142K/yr

NVIDIA is at the forefront of the AI and robotics revolution, and they are seeking a Senior Robotics Research Scientist to join their Seattle Robotics Lab. The role involves developing and ...

NVIDIA AI

Senior Compiler Engineer - PVA

Santa Clara, CA · On-site

$122K - $168K/yr

Job Summary : NVIDIA is now looking for a Senior Compiler Engineer to join their Programmable ... Explore the latest breakthroughs made possible with AI. Founded in , the company is headquartered ...

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Infographic showing various job openings at Nvidia Ai in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% Physical job distribution.

Senior AI Solutions Architect - Semiconductors

NVIDIA AI

Santa Clara, CA • On-site

Full-time

Posted 26 days ago

Job description

Job Summary:
NVIDIA AI is a leader in transforming computer graphics and accelerated computing, now focusing on AI's potential in the next era of computing. They are seeking a Senior AI Solutions Architect to support Semiconductor accounts, acting as a technical advisor to enhance workflows in chip design and manufacturing using NVIDIA's advanced technologies.
Responsibilities:
• Support Business Development and Sales teams as part of a small Solutions Architecture team, partnering with Industry Business leads, Account Managers, and Developer Relations managers to drive ecosystem success across Semiconductor accounts (EDA vendors, chip designers, semiconductor-equipment OEMs, and fabs).
• Work directly with EDA/CAD developers and customer design and manufacturing teams in a customer-facing setting.
• Help developers GPU-accelerate and scale EDA workflows — place-and-route, circuit simulation, timing and power analysis, DRC/LVS, and verification — and computational lithography (e.g., NVIDIA cuLitho).
• Apply ML/DL to semiconductor manufacturing: defect detection, inspection and metrology, yield optimization, and process control.
• Analyze EDA and manufacturing application architectures and find opportunities for acceleration.
• Provide feedback and collaborate with engineering, product, and research teams.
• Deliver trainings, hackathons, and technical demonstrations on NVIDIA solutions and platforms.
Qualifications:
Required:
• MS/PhD in Electrical or Computer Engineering, Materials Science, Applied Physics, Computational Science, or a related technical field (or equivalent experience).
• 4+ years in semiconductor design, EDA, or semiconductor manufacturing — chip design/verification, TCAD, lithography, or fab process/yield engineering — and/or AI/ML applied to these domains.
• Familiarity with EDA flows and tools (e.g., Cadence, Synopsys, Siemens EDA) and/or computational lithography, TCAD, or inspection/metrology systems.
• Experience in algorithm programming using languages like Python and C/C++, with familiarity GPU-accelerating compute-intensive workloads.
• Development experience using major AI frameworks (e.g., PyTorch, TensorFlow) for vision, ML, or manufacturing use cases.
• Familiarity with accelerated computing platforms, GPU-based distributed systems, and HPC clusters.
• Familiarity with containers, numerical libraries, modular software design, version control, GitHub.
• Experience designing, prototyping, and building complex AI/ML-based solutions for customers; able to reason across components such as data pipelines, models, compute, networking, and orchestration.
• Solid written and oral communication skills and familiarity with collaborative environments.
• Team player who can learn, react, and adapt quickly, with an attitude to work in a fast-paced environment.
Preferred:
• Experience with computational lithography (NVIDIA cuLitho) or GPU-accelerated EDA flows.
• Experience applying ML/DL to defect inspection, metrology, or yield and process optimization in a fab or equipment setting.
• Development experience with NVIDIA software libraries and GPUs, including CUDA and CUDA-X libraries.
• Experience with Kubernetes, distributed training, and large-scale inference.
• Experience supporting or using PCIe accelerators such as GPUs, FPGAs, DSPs from evaluation to production stages.
Company:
Explore the latest breakthroughs made possible with AI. Founded in , the company is headquartered in Santa Clara, CA, US, , with a team of 10001+ employees. The company is currently Late Stage.

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