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Neural Engineering Jobs in Houston, TX (NOW HIRING)

Urnet Inc

Engineer

Houston, TX · On-site

$100K - $150K/yr

Strong understanding of Artificial Neural Networks and their applications in systems engineering. Preferred Qualifications: * Master's degree in a relevant field. * Experience with machine learning ...

Beth Page tech

Senior Machine Learning Engineer

Houston, TX · On-site

$99K - $137K/yr

Senior Machine Learning Engineer Location: Houston, TX Environment: Standard, 5-days onsite : Must ... Deep Neural Networks (DNN): * Hands-on experience with CNN, RNN, Graph Neural Networks, and ...

Bot Auto

Senior ML/RL Engineer, Behavior Planning

Houston, TX · On-site

$99K - $137K/yr

... Engineer to develop their unified behavioral architecture. This role involves bridging the gap ... Advance our state-of-the-art neural architectures to improve spatial reasoning, long-horizon ...

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How much do neural engineering jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for neural engineering in Houston, TX is $18.44, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $19.95 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.

Is neural engineering a good career?

Neural engineering is a growing interdisciplinary field that combines neuroscience, engineering, and computer science to develop technologies like brain-computer interfaces and neural prosthetics. It offers opportunities in research, healthcare, and industry, often requiring advanced degrees and technical skills. The field is expected to expand as neurotechnology advances and healthcare needs increase.

What can you do with a neural engineering degree?

A neural engineering degree prepares individuals for careers in developing brain-computer interfaces, neuroprosthetics, and neural signal processing. Graduates often work in research, healthcare, or technology companies, utilizing skills in neuroscience, engineering, and programming to innovate medical devices and neural systems.

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 Houston, TX as of August 2026, with employment types broken down into 5% Internship, 79% Full Time, and 16% Contract. Highlights an 94% In-person, and 6% Hybrid job distribution, with an average salary of $38,365 per year, or $18.4 per hour.

Engineer

Urnet Inc

Houston, TX • On-site

$100K - $150K/yr

Full-time

Re-posted 11 days ago

Job description

About the Role:

As an Engineer in the Information industry, you will play a pivotal role in designing and implementing advanced systems that leverage Artificial Neural Networks to solve complex problems. Your work will directly contribute to the development of innovative solutions that enhance operational efficiency and drive technological advancements. You will collaborate with cross-functional teams to ensure that systems are robust, scalable, and meet the highest standards of quality. This position requires a deep understanding of C++ programming to develop and optimize algorithms that power our neural network models. Ultimately, your contributions will help shape the future of our technology offerings and improve user experiences across various applications.

Minimum Qualifications:

  • Bachelor's degree in Engineering, Computer Science, or a related field.
  • Proven experience in developing applications using C++.
  • Strong understanding of Artificial Neural Networks and their applications in systems engineering.

Preferred Qualifications:

  • Master's degree in a relevant field.
  • Experience with machine learning frameworks such as TensorFlow or PyTorch.
  • Familiarity with software development methodologies and tools.

Responsibilities:

  • Design, develop, and implement algorithms using Artificial Neural Networks to address specific engineering challenges.
  • Write and maintain high-quality C++ code to support system functionalities and performance optimization.
  • Collaborate with software developers, data scientists, and other engineers to integrate neural network solutions into existing systems.
  • Conduct system testing and validation to ensure reliability and accuracy of the implemented solutions.
  • Document technical specifications and provide training to team members on new technologies and methodologies.

Skills:

The required skills in Artificial Neural Networks will be utilized daily to create models that can learn from data and improve over time, ensuring that our systems remain cutting-edge. Proficiency in C++ is essential for writing efficient code that can handle complex computations and large datasets, which is a core part of our engineering processes. Systems engineering skills will be applied to integrate various components of our technology stack, ensuring seamless operation and performance. Additionally, preferred skills such as experience with machine learning frameworks will enhance your ability to implement state-of-the-art solutions. Overall, these skills will enable you to contribute effectively to projects that require innovative thinking and technical expertise.