1

Ai Chip Jobs in Oregon (NOW HIRING)

Senior Applied AI Engineer

Hillsboro, OR · On-site

$133K - $175K/yr

As part of Nvidia's applied AI team for chip design, you will have the opportunity to tap into the unlimited potential of AI and change the landscape of the chip industry. Our team operates at the ...

Senior Applied AI Engineer

Hillsboro, OR · On-site

$113K - $156K/yr

As part of Nvidia's applied AI team for chip design, you will have the opportunity to tap into the unlimited potential of AI and change the landscape of the chip industry. Our team operates at the ...

Senior Platform AI Engineer

OR · On-site +1

$104K - $143K/yr

Exposure to silicon design, methodology, validation or EDA toolchains, especially the cadence of chip development lifecycles. Experience building or operating AI platforms within a silicon ...

Applied AI Engineer

OR · On-site +1

Experience working within a silicon development environment, with exposure to chip and system ... Familiarity with modern AI technologies and methodologies for crafting and launching LLMs with ...

Applied AI Engineer

OR · On-site +1

Experience working within a silicon development environment, with exposure to chip and system ... Familiarity with modern AI technologies and methodologies for crafting and launching LLMs.

Applied AI Engineer

OR · On-site +1

Experience working within a silicon development environment, with exposure to chip and system ... Ability to translate innovative AI research into practical, high-impact production tools.

The complexity of chip development has greatly increased over the years. We are now packing tens of ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive ...

The complexity of chip development has greatly increased over the years. We are now packing tens of ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive ...

The complexity of chip development has greatly increased over the years. We are now packing tens of ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive ...

Experience with GPU or AI accelerator architecture, including platform aspects, off-chip I/O technologies, and networked multi-GPU systems * Knowledgeable in modern packaging technologies, and their ...

next page

Showing results 1-20

Ai Chip information

What is an AI chip?

AI chips are specialized hardware components designed to accelerate artificial intelligence workloads, such as machine learning and deep learning tasks. Unlike traditional CPUs, AI chips are optimized for processing large volumes of data in parallel, making them highly efficient for neural network computations. These chips are commonly used in data centers, smartphones, autonomous vehicles, and edge devices to enable faster and more energy-efficient AI processing.

What are some common challenges faced by professionals working in AI chip development, and how can they be addressed?

Professionals in AI chip development often encounter challenges such as balancing high computational performance with power efficiency, keeping up with rapid technological advancements, and integrating hardware with evolving AI algorithms. Collaboration between hardware engineers, software developers, and data scientists is essential to ensure that chips meet both performance and functional requirements. Staying current through ongoing learning and participating in cross-functional teams can help address these challenges and contribute to successful AI chip projects.

What are the key skills and qualifications needed to thrive as an AI chip engineer, and why are they important?

To thrive as an AI Chip Engineer, you need a solid background in electrical engineering, computer architecture, and experience with hardware design, typically supported by a relevant degree. Familiarity with hardware description languages (such as Verilog or VHDL), EDA tools, and knowledge of semiconductor fabrication processes are crucial technical requirements. Attention to detail, strong problem-solving abilities, and effective teamwork skills help you excel in complex project environments. These competencies are vital for developing high-performance, efficient AI chips that power modern artificial intelligence applications.

What is the difference between Ai Chip vs AI Hardware Engineer?

AspectAi ChipAI Hardware Engineer
Required CredentialsBachelor's or higher in Electrical Engineering, Computer Engineering, or related fields; knowledge of VLSI designBachelor's or higher in Electrical Engineering, Computer Engineering, or related fields; experience with hardware design and testing
Work EnvironmentDesign labs, manufacturing facilities, R&D centersDesign labs, testing facilities, R&D centers
Employer & Industry UsageTech companies, semiconductor firms, AI hardware startupsTech companies, semiconductor companies, research institutions

While both roles involve hardware and AI technology, an Ai Chip focuses on designing and developing AI-specific chips, whereas an AI Hardware Engineer works on the broader hardware systems that support AI applications, including integration and testing.

Which AI chip job is high paying?

Senior AI chip design engineers and hardware architects typically earn the highest salaries in AI chip jobs due to their specialized skills in semiconductor design, deep learning hardware, and system integration. These roles often require advanced degrees and experience with tools like FPGA or ASIC development, and they can command six-figure salaries depending on the company and location.

What are popular job titles related to Ai Chip jobs in Oregon?

For Ai Chip jobs in Oregon, the most frequently searched job titles are:

What cities in Oregon are hiring for Ai Chip jobs?

Cities in Oregon with the most Ai Chip job openings:

Infographic showing various Ai Chip job openings in Oregon as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, 2% Contract, and 1% Nights. Highlights an 64% Physical, 3% Hybrid, and 33% Remote job distribution.

Senior AI Solutions Architect - Semiconductors

Nvidia

OR • On-site, Remote

Full-time

Posted 7 days ago


Key responsibilities

  • Support semiconductor accounts by acting as a technical advisor to EDA/CAD developers and customer teams, embedding NVIDIA accelerated computing and AI into workflows.

  • Help developers GPU-accelerate and scale EDA workflows such as place-and-route, circuit simulation, timing and power analysis, DRC/LVS, and verification, as well as computational lithography.

  • Deliver trainings, hackathons, and technical demonstrations on NVIDIA solutions and platforms.


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing.

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.

Come join the team and see how you can make a lasting impact on the world. We are looking for a Senior Solutions Architect to support our Semiconductor accounts - the chip-design houses, EDA software vendors, semiconductor-equipment makers, and fabs adopting accelerated computing across chip design, verification, lithography, and manufacturing. In this role you will be a trusted technical advisor to EDA/CAD developers and customer engineering teams, embedding NVIDIA accelerated computing, computational lithography (cuLitho), and AI into design, verification, and manufacturing workflows.

You will play a direct role in improving application performance, accelerating design and yield cycles, and establishing the technical foundation required for next-generation semiconductor systems. What you'll be doing: 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. What we need to see: 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.

Ways to stand out from the crowd: 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. NVIDIA is widely considered to be one of the technology world's most desirable employers.

We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you. #NALASAHiring Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until July 20, 2026.

This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer.

As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.


What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US