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Neural Engineering Jobs (NOW HIRING)

Nvidia

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Neural reconstruction and Gaussian Splatting are changing how 3D worlds are collected, represented ... Engineering, Applied Math, Robotics, Computer Vision, Machine Learning, or a related field (or ...

Nvidia

Neural reconstruction and Gaussian Splatting are changing how 3D worlds are collected, represented ... Engineering, Applied Math, Robotics, Computer Vision, Machine Learning, or a related field (or ...

Rivian

Neural Network Microarchitect

Palo Alto, CA

$218K - $312K/yr

Mentor engineers across architecture and implementation disciplines and raise the technical bar for neural network accelerator design at Rivian. Qualifications * Deep expertise in computer ...

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How much do neural engineering jobs pay per hour?

As of Jul 6, 2026, the average hourly pay for neural engineering in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 per hour, depending on experience, location, and employer.

What is neural engineering?

Neural engineering is a multidisciplinary field that combines engineering, neuroscience, and computational approaches to understand, repair, enhance, or interface with the nervous system. Neural engineers develop devices such as brain-computer interfaces, neural prosthetics, and neurostimulation systems to restore or improve neural function. This field plays an important role in advancing treatments for neurological disorders and in creating technologies that bridge the gap between machines and the human brain.

What are the key skills and qualifications needed to thrive as a Neural Engineer, and why are they important?

To thrive as a Neural Engineer, you need a strong background in neuroscience, biomedical engineering, and signal processing, typically supported by an advanced degree in a related field. Familiarity with programming languages (such as MATLAB or Python), neuroimaging tools, and hardware platforms used for neural interfacing is essential. Excellent problem-solving skills, collaboration, and clear communication set standout professionals apart in this multidisciplinary environment. These skills are crucial for developing innovative neural technologies and translating research into effective clinical or commercial solutions.

What Are Jobs in Neural Engineering?

Jobs in neural engineering focus on helping research and design biomedical devices like prosthetic limbs and artificial organs. In these roles, you may determine the best way to implement designs for each situation, figure out the best way to link mechanical systems to the human brain, and find the most cost-effective ways to build devices. Neural engineering differs from engineering regular prosthetic limbs in that they receive instructions directly from the brain and often send information back, rather than simply being attached to the body. This often involves programming specialized software and figuring out how to make devices that can teach the brain how to use them. In recent years, neural engineering has started to move out of the medical realm, and there may be more jobs of that nature in the future. Neural engineering is a specific type of biomedical engineering, but should not be confused with jobs in the broader category.

What are some common interdisciplinary challenges faced by neural engineers when collaborating with clinicians and data scientists?

Neural engineers frequently work on teams that include clinicians, data scientists, and hardware specialists, which can present unique interdisciplinary challenges. Effective communication is essential, as team members often have different technical backgrounds and priorities—clinicians focus on patient outcomes, while data scientists emphasize analytical accuracy. Bridging the gap between clinical needs and technical feasibility requires adaptability, openness to feedback, and a willingness to learn new concepts. Building strong collaborative relationships and participating in regular cross-functional meetings can help ensure that project goals are clearly understood and met by all stakeholders.
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Neural Engineering jobs near you
Infographic showing various Neural Engineering job openings in the United States as of June 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 71% Physical, 2% Hybrid, and 27% Remote job distribution, with an average salary of $40,174 per year, or $19.3 per hour.

Neural Network Specialist

Special Projects Engineering LLC

Bellevue, WA • On-site, Remote

$150K - $170K/yr

Full-time

Posted 5 days ago

Be an early applicant

Job description

About Special Projects Engineering LLC

At Special Projects Engineering, we rethink problems from the ground up. We’re a small, high-impact team based in Seattle focused on applying advanced AI to complex, often unconventional challenges. Our work spans autonomous systems, predictive infrastructure, synthetic biology, and defense-grade automation. If it’s ambitious, technical, and hasn’t been done before, we’re probably already working on it.

What You’ll Do

As a Neural Network Specialist, you’ll be responsible for designing and optimizing deep learning architectures that push the limits of what’s technically possible. You’ll collaborate closely with the CTO and a diverse team of engineers, scientists, and domain experts to move ideas from prototypes to deployment.

Key responsibilities:

  • Design, train, and evaluate neural network architectures for real-world use

  • Work with unstructured data including visual, auditory, textual, and time-series formats

  • Develop systems for tasks like perception, decision-making, prediction, and control

  • Optimize models for performance, scalability, and deployment on various platforms

  • Rapidly iterate on ideas while balancing reliability and experimental curiosity

  • Collaborate with hardware, embedded, and software teams to integrate models into real systems

  • Contribute to the ML roadmap, infrastructure, and toolchain

What We’re Looking For

  • 5+ years of experience in deep learning or applied neural network research

  • Strong Python skills, with additional experience in C++ or Rust preferred

  • Expertise in PyTorch, TensorFlow, or JAX

  • Solid understanding of training techniques, loss functions, evaluation metrics, and deployment strategies

  • Experience with one or more domains like computer vision, NLP, reinforcement learning, or multimodal models

  • Comfortable owning projects from research through production

  • Bonus if you’ve worked with robotics, embedded AI, or unusual sensor inputs

Why You Might Care

  • Competitive salary and meaningful equity

  • Remote-friendly with flexible hours

  • Full medical, dental, and vision coverage

  • Access to top-tier GPU hardware

  • Small team, zero bureaucracy, high ownership

  • Projects that are genuinely interesting and occasionally a little insane

If you're serious about pushing neural networks into places they've never gone before, apply now and let's get to work.