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Neuromorphic Computing Circuit Design Jobs (NOW HIRING)

Intel

CPU Circuit Design Engineer

Austin, TX · On-site

$141K - $269K/yr

Works with design domains RTL/circuit/SD to converge to timing targets with no compromise on ... computing experiences. Posting Statement:All qualified applicants will receive consideration for ...

Intel Corporation

CPU Circuit Design Engineer

Austin, TX · On-site

$141K - $269K/yr

Works with design domains RTL/circuit/SD to converge to timing targets with no compromise on ... of computing experiences. Posting Statement: All qualified applicants will receive consideration ...

Intel

Senior AI Software Architect - Runtime

Hillsboro, OR

$141K - $191K/yr

For nearly a decade, Intel's Neuromorphic Computing Lab-together with a global ecosystem of 250 ... Experience in HW/SW co-design, hardware simulator development, or software bring-up for emerging ...

Intel

Senior AI Software Architect - Runtime

Austin, TX · On-site

$128K - $174K/yr

For nearly a decade, Intel's Neuromorphic Computing Lab-together with a global ecosystem of 250 ... Experience in HW/SW co-design, hardware simulator development, or software bring-up for emerging ...

Nvidia

OR · Hybrid

$103K - $139K/yr

... computing. More recently, our advancements in artificial intelligence and deep learning have ... Drive the design and physical implementation of digital and/or mixed-signal analog circuit IPs for ...

Nvidia

Senior Circuit Design Engineer

Santa Clara, CA · Hybrid

$122K - $164K/yr

... computing. More recently, our advancements in artificial intelligence and deep learning have ... Drive the design and physical implementation of digital and/or mixed-signal analog circuit IPs for ...

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$67K

$121.8K

$172.5K

How much do neuromorphic computing circuit design jobs pay per year?

As of Jun 7, 2026, the average yearly pay for neuromorphic computing circuit design in the United States is $121,794.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,000.00 and $141,500.00 per year, depending on experience, location, and employer.

What is neuromorphic computing circuit design?

Neuromorphic computing circuit design is the process of creating electronic circuits that mimic the architecture and functionality of the human brain. These circuits use specialized hardware, such as analog or digital spiking neural networks, to process information in ways similar to biological neurons and synapses. The goal is to achieve highly efficient, low-power computation for tasks like pattern recognition, sensory processing, and machine learning. Neuromorphic circuits are increasingly used in artificial intelligence applications where conventional computing struggles with speed or energy efficiency.

What are some common challenges faced by professionals in neuromorphic computing circuit design, and how can they be addressed?

Professionals in neuromorphic computing circuit design often encounter challenges related to integrating novel architectures with traditional CMOS processes, ensuring energy efficiency, and managing the variability of emerging devices like memristors. Effective solutions include staying updated with the latest semiconductor fabrication techniques, collaborating closely with interdisciplinary teams (such as neuroscientists and software engineers), and leveraging simulation tools to prototype and validate designs before fabrication. Proactively participating in industry conferences and academic collaborations can also help designers stay ahead of evolving challenges in this rapidly changing field.

What companies are working on neuromorphic computing?

Several companies are actively developing neuromorphic computing technologies, including Intel, IBM, BrainChip, and Qualcomm. These organizations focus on designing specialized hardware and circuits that mimic neural structures, often integrating neuromorphic chips into AI and machine learning applications.

What are the key skills and qualifications needed to thrive as a Neuromorphic Computing Circuit Designer, and why are they important?

To thrive as a Neuromorphic Computing Circuit Designer, a strong background in electrical engineering, semiconductor device physics, and neural network principles is essential, typically supported by an advanced degree such as a Master’s or PhD. Proficiency with CAD tools (e.g., Cadence, Synopsys), hardware description languages (HDL), and simulation software is critical for designing and testing circuits. Creative problem-solving, interdisciplinary collaboration, and attention to detail are vital soft skills that distinguish top performers in this field. These skills and qualities are crucial for developing innovative, efficient circuits that mimic brain-like processing, pushing the boundaries of artificial intelligence hardware.
Infographic showing various Neuromorphic Computing Circuit Design job openings in the United States as of May 2026, with employment types broken down into 4% Internship, 82% Full Time, 6% Part Time, 4% Temporary, 2% Contract, and 2% Nights. Highlights an 93% Physical, 5% Hybrid, and 2% Remote job distribution, with an average salary of $121,794 per year, or $58.6 per hour.
PostDoc - Machine Learning

PostDoc - Machine Learning

Brookhaven National Laboratory

Upton, NY • On-site

Full-time

Posted 8 days ago

Job description

Job Summary:
Brookhaven National Laboratory is a multidisciplinary laboratory that delivers discovery science and transformative technology. They are inviting exceptional candidates to apply for a post-doctoral research associate position in machine learning and artificial intelligence, focusing on conducting research in brain-inspired neuromorphic computing and collaborating on scientific and security problems of interest to the Department of Energy.
Responsibilities:
• Conduct research in brain-inspired neuromorphic computing for various problems relating to microelectronics and scientific discovery.
• Work in interdisciplinary collaborations with subject matter experts on various aspects of scientific data generation and processing and methods evaluation.
• Formulate high-quality research ideas and directions in collaboration with mentors in the department.
• Communicate research progress, challenges, and achievements, and engage within and beyond the department on new potential collaborations.
Qualifications:
Required:
• Ph.D. in computer science or a related field (e.g., engineering, applied mathematics, statistics, physics, etc.) awarded within the past 5 years.
• Strong theoretical understanding and practical experience in neuromorphic computing and/or AI/ML.
• Strong publication record.
• Excellent programming and computer science or electrical engineering skills.
Preferred:
• Experience with neuromorphic computing.
• Experience with hardware design using emerging devices (FeFET, ReRAM, SPD, etc.)
• Experience working in multidisciplinary collaborations.
Company:
Brookhaven National Laboratory is a multi-purpose research institution focused on questions in basic and applied science. Founded in 1947, the company is headquartered in Upton, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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