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Ai Chip Design Rtl Jobs in Milpitas, CA (NOW HIRING)

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Lead RTL Design Engineer

Sunnyvale, CA · On-site

$175 - $275/hr

Drive all aspects of chip design, including Functional Specification, Micro-architecture, RTL ... Publish and open source their cutting-edge AI research. * Work on one of the fastest AI ...

Google Inc.

RTL Design Engineer, TPU

Sunnyvale, CA · On-site

$163 - $237/hr

Experience with chip management, clocking, reset, and peripherals such as I2C, SPI, UART ... AI/ML‑driven systems. US compensation: $163,000-$237,000 (USD) + 15% bonus target + equity ...

Brahma Consulting Group

Head of AI

Palo Alto, CA

$350K - $500K/yr

You should bring deep expertise in ML for chip design, as well as leadership experience in high ... Architect and deploy novel agent-based systems, including fine-tuning models for RTL Code ...

Brahma Consulting Group

Head of Hardware

Palo Alto, CA · On-site

$145K - $191K/yr

... AI-driven chip design in a fast-paced, cutting-edge environment. Key Responsibilities * Lead ... Oversee all hardware engineering efforts, setting the vision and strategy for RTL development and ...

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Ai Chip Design Rtl information

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$93.8K

$162.4K

$212.7K

How much do ai chip design rtl jobs pay per year?

As of Sep 5, 2026, the average yearly pay for ai chip design rtl in Milpitas, CA is $162,415.00, according to ZipRecruiter salary data. Most workers in this role earn between $158,500.00 and $158,500.00 per year, depending on experience, location, and employer.

What is an AI Chip Design RTL engineer?

AI Chip Design RTL (Register Transfer Level) engineers are specialists who design the digital logic for chips used in artificial intelligence applications. They use hardware description languages like Verilog or VHDL to create and validate the architecture and functionality of these chips before they are manufactured. Their work ensures that AI processors are efficient, high-performing, and meet the requirements of modern AI workloads. RTL engineers collaborate closely with verification, software, and hardware teams to optimize chip performance and power consumption.

What skills and qualifications are needed to thrive as an AI Chip Design RTL engineer?

To thrive as an AI Chip Design RTL Engineer, you need a solid background in digital design, computer architecture, and proficiency in Hardware Description Languages (HDLs) like Verilog or VHDL, often supported by a degree in electrical or computer engineering. Experience with simulation tools (e.g., ModelSim, Synopsys), ASIC/FPGA design flows, and relevant certifications are highly valued. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills help you excel in collaborative and complex design environments. These competencies are crucial for creating efficient, reliable AI hardware that meets performance and power requirements in a fast-evolving field.

What are common challenges faced by AI Chip Design RTL engineers during the verification process?

AI Chip Design RTL engineers often encounter challenges in ensuring their designs meet complex functional and performance requirements, especially given the rapid pace of AI hardware advancements. Verification can be particularly demanding due to the need to simulate and test intricate AI workloads, manage large datasets, and debug subtle timing or logic errors. Collaboration with verification teams, system architects, and software engineers is essential to address these issues efficiently and to ensure seamless integration of the RTL code into the broader chip design. Staying up-to-date with the latest verification tools and methodologies is also crucial for success in this role.

What is the difference between Ai Chip Design Rtl vs Ai Chip Verification Engineer?

AspectAi Chip Design RtlAi Chip Verification Engineer
Primary FocusDeveloping and implementing Register Transfer Level (RTL) code for AI chipsVerifying and validating RTL designs to ensure functionality
Skills RequiredHDL languages (Verilog/VHDL), digital design, FPGA/ASIC knowledgeSimulation, testbench creation, debugging, scripting skills
Work EnvironmentDesign teams, hardware development labs, EDA toolsVerification teams, simulation environments, test setups
CertificationsHardware design certifications, FPGA/ASIC trainingVerification methodologies, UVM, SystemVerilog certifications

While Ai Chip Design Rtl focuses on creating the hardware description code for AI chips, Ai Chip Verification Engineer ensures that the RTL design functions correctly through rigorous testing. Both roles require knowledge of HDL languages and work closely within hardware development teams, but their core responsibilities differ—design versus verification.

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Ai Chip Design Rtl jobs near you
Infographic showing various Ai Chip Design Rtl job openings in Milpitas, CA as of August 2026, with employment types broken down into 81% Full Time, 13% Part Time, 2% Temporary, and 4% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $162,415 per year, or $78.1 per hour.

Senior ASIC Design Engineer - Agentic AI

Nvidia Corporation

Santa Clara, CA • On-site

Full-time

Re-posted 11 days ago

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 is seeking ASIC Design Engineers with experience in agentic AI to help design and implement the world's leading SoC's and GPU's. As part of NVIDIA's "AI for chip design" team, you will have the opportunity to tap into the unlimited potential of AI and change the landscape of chip design at NVIDIA and throughout the industry. This position offers the opportunity to have a real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. We have crafted a team of exceptional people stretching around the globe, whose mission is to push the frontiers of what is possible today and define the platform for the future of computing. Our team operates at the intersection of research, engineering, and product development, transforming innovative ideas and research breakthroughs into real-world solutions. If you're passionate about the latest research and cutting-edge technologies shaping generative AI, this role and team offer a great opportunity to be at the forefront of innovation.
What you'll be doing:
  • As a member of the GPU Design Methodology team, you will document and deliver design guidelines that will help the ASIC team implement high performance, area and power efficient RTL to achieve design targets and specifications.
  • As part of the AI for Chip Design team, you will develop agentic AI solutions to craft the micro-architecture, implement the RTL, and deliver a fully verified, synthesis/timing clean design.
  • Collaborate and coordinate with other designers as well as tool and flow owners to make sure design guidelines and agentic solutions meet their requirements.
  • Make a difference by using AI technologies to tackle complex problems in chip design, driving innovation and meaningful impact across the industry.
  • Drive impact by designing and deploying LLM-powered solutions for engineering assistants and multi-turn, multi-modal dialogue systems.
  • Stay ahead by engaging with the latest advancements in machine learning and AI to create powerful solutions.

What we need to see:
  • Master's or PhD degree in Electrical Engineering, Computer Science/Engineering, or a related field (or equivalent experience).
  • 8+ years of meaningful work experience.
  • Experience in micro-architecture and RTL development (Verilog) in complex designs.
  • Deep understanding of ASIC design flow including RTL design, verification, logic synthesis and timing analysis.
  • Exposure to Digital systems and VLSI design, Computer Architecture, and Computer Arithmetic is required.
  • Proficiency in rapid prototyping using Python with strong foundational knowledge of data structures, algorithms, and software engineering principles.
  • Experience with fine-tuning large language models, building advanced multi-agent systems, RAG pipelines and vector databases.
  • Strong analytical, communication, and interpersonal skills, with a proven track record to thrive in dynamic, product-focused, and distributed teams.
  • A proactive approach to problem-solving and a willingness to acquire new skills and knowledge as needed to achieve results.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking people in the world working for us. We inspire our engineers to build solutions for the problems faced by our customers. Are you creative? Do you love the challenge of continuously crafting the fastest, most efficient GPUs while driving innovation across multiple fields? If so, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 30, 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

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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

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