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Neural Engineering Jobs in Florida (NOW HIRING)

CYNET SYSTEMS

Software Developer 1

Orlando, FL · On-site

$30 - $37/hr

... engineering data management system followed by developing Large Language Model (LLM) assistants to ... Solid understanding of Computer Vision and Neural Network concepts. * Understanding of relational ...

Pwc

AI Engineer

Tampa, FL · On-site

$50K - $112K/yr

... neural networks and deep learning methods for advanced AI applications - Managing data quality and ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

Pwc

AI Engineer

Miami, FL · On-site

$50K - $112K/yr

... neural networks and deep learning methods for advanced AI applications - Managing data quality and ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

Opendoor

Applied Scientist AI/ML

Miami, FL · On-site

Responsibilities : • Design and deploy architectural improvements to our deep neural network (DNN ... Required : • Strong software engineering and coding skills in Python, with experience ...

Opendoor

Applied Scientist AI/ML

Miami, FL · On-site

Responsibilities : • Design and deploy architectural improvements to our deep neural network (DNN ... Required : • Strong software engineering and coding skills in Python, with experience ...

Pwc

AI Engineer

Boca Raton, FL · On-site

$50K - $112K/yr

... neural networks and deep learning methods for advanced AI applications - Managing data quality and ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

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Neural Engineering information

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How much do neural engineering jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for neural engineering in Florida is $14.43, according to ZipRecruiter salary data. Most workers in this role earn between $12.02 and $15.62 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 Florida as of August 2026, with employment types broken down into 86% Full Time, and 14% Part Time. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $30,022 per year, or $14.4 per hour.

Sr. AI/ML Engineer (LLM)

Bomnin Automotive Group

Miami, FL

Full-time

Re-posted 8 days ago

Job description

Job description

Company Description

Dealer Automation Technologies is a leading Information Technology Services company that provides Software as a Service (SaaS) solutions for the automotive industry. The company specializes in Process Automation, Advanced Analytics, and Augmented Intelligence to redefine dealership operations. With a focus on intuitive user experiences and cutting-edge technologies, Dealer Automation Technologies is paving the way for innovation in the sector. Combining the agility of a startup with the expertise and business acumen of seasoned leaders, the company operates without dependence on legacy systems, fostering a dynamic and innovative work culture.

Role Description

This is a full-time, on-site role located in Miami, FL, for a Senior AI/ML Engineer specializing in Large Language Models (LLMs) to join our team. You will play a key role in designing and implementing workflows that leverage large language models (LLMs, LAMs, LMMs, LVLMs, etc.) to automate processes and drive innovation in our products. The ideal candidate will have a deep understanding of NLP, experience with foundational models, and a flexible, problem-solving mindset. You will collaborate closely with cross-functional teams, contributing to the development of scalable AI driven solutions. Other primary responsibilities include designing and implementing machine learning models, particularly in natural language processing and large language models, building scalable algorithms, conducting research on neural networks, and evaluating model performance. Additionally, the engineer will collaborate with cross-functional teams to ensure seamless integration of AI/ML components into the company’s software offerings.

Major Areas of Responsibility

  • Design, Implement, and optimize workflows that incorporate large language models to automate and enhance product features.
  • Leverage existing foundational models and adapt them to fit into various product requirements, ensuring alignment with business goals.
  • Collaborate with product managers, data scientist, and software engineers to integrate LLM-based automation into scalable solutions.
  • Create and architect interpreters, Agented Systems, and integrate multi-hop RAG and other LLM experiences into existing systems to coordinate knowledge responses.
  • Research and evaluate new technologies and methodologies in the LLM space to continuously improve product automation.
  • Work on the customization and fine-tunning of models to optimize performance for specific use cases.
  • Develop, test, and deploy LLM-based services in production environments.
  • Provide AI/ML technical leadership and mentorship to other engineers on the team.
  • Ensure that LLM integrations are efficient, scalable, and secure, adhering to industry best practices.

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