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Remote Neural Engineer Jobs (NOW HIRING)

Ivix

Deployment Engineer - US

IVIX employs a variety of AI tools (deep neural networks, large language models, and predictive ... East Coast US-based (remote)

Mastech Digital

AI Engineer

Pittsburgh, PA · Remote

$70 - $76/hr

Remote - US, Canada, India Salary: $70.00-$76.00/Hourly Role: AI Engineer Primary Skills: Python ... neural network architectures such as Tacotron, FastSpeech, WaveNet, or similar. - Collect ...

Zencastr

Senior Machine Learning Engineer (Remote)

New York, NY · On-site +1

$114K - $157K/yr

You'll join a team of hardworking engineers that are passionate about understanding what drives ... neural networks * Significant experience with machine learning libraries like PyTorch, Tensorflow ...

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$203K

How much do remote neural engineer jobs pay per year?

As of Jul 17, 2026, the average yearly pay for remote neural engineer in the United States is $111,632.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,500.00 and $132,500.00 per year, depending on experience, location, and employer.

What is a Remote Neural Engineer?

A Remote Neural Engineer is a professional who designs, develops, and maintains neural engineering systems—such as brain-computer interfaces or neural prosthetics—while working remotely. They often collaborate with multidisciplinary teams to create solutions that interface with the nervous system, using expertise in neuroscience, biomedical engineering, and software development. Remote Neural Engineers may work from home or distributed locations, utilizing digital tools to analyze neural data, develop algorithms, and contribute to research or product development in the neural technology field.

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

To thrive as a Remote Neural Engineer, you need a solid background in neuroscience, biomedical engineering, or electrical engineering, often supported by a relevant degree or advanced certification. Proficiency with neural signal processing software, programming languages like Python or MATLAB, and brain-computer interface (BCI) systems is typically required. Strong problem-solving skills, attention to detail, and effective virtual communication are vital soft skills in this role. These skills and qualities are essential for developing, analyzing, and troubleshooting complex neural systems while collaborating with teams remotely.

What engineers make $300,000 a year?

Senior neural engineers or specialized AI and machine learning engineers in high-demand industries can earn $300,000 or more annually, especially with extensive experience, advanced skills in deep learning, and working in competitive tech environments. Such roles often require advanced degrees, certifications, and a strong portfolio of research or projects.

How do Remote Neural Engineers typically collaborate with cross-functional teams while working off-site?

Remote Neural Engineers frequently use digital collaboration tools such as video conferencing, shared code repositories, and project management platforms to stay connected with colleagues in neuroscience, software development, and data science. Regular virtual meetings and asynchronous communication help ensure alignment on project goals, data analysis, and protocol development. This structure allows for flexibility, but also requires proactive communication and strong organizational skills to manage complex, interdisciplinary tasks from a distance.

What engineers make $500,000?

Senior neural engineers or specialized AI and machine learning engineers in high-demand industries can earn $500,000 or more annually, especially with extensive experience, advanced skills in deep learning, and working in competitive tech sectors. Compensation often includes base salary, bonuses, and stock options, particularly at leading tech companies or startups with significant funding.

What is the difference between Remote Neural Engineer vs Remote Data Scientist?

AspectRemote Neural EngineerRemote Data Scientist
Required CredentialsDegree in neuroscience, biomedical engineering, or related fields; knowledge of neural interfacesDegree in computer science, statistics, or related fields; proficiency in data analysis
Work EnvironmentResearch labs, tech companies, healthcare institutions with focus on neural dataTech firms, finance, healthcare, analyzing large datasets
Industry UsageNeuroscience, biomedical engineering, neurotechnologyTechnology, finance, healthcare, research
Common Search/ComparisonYesYes

Remote Neural Engineers focus on developing and implementing neural interfaces and understanding neural systems, often requiring knowledge of neuroscience and biomedical engineering. Remote Data Scientists analyze large datasets to extract insights, typically with skills in statistics and programming. While both roles involve technical expertise and data analysis, Neural Engineers are more specialized in neural technologies, whereas Data Scientists have a broader application across industries.

Is neuroengineering a good career?

Neuroengineering is a growing 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 career can be rewarding for those interested in innovative medical solutions and interdisciplinary work.

Can you work remotely as an AI engineer?

Remote work is common for AI engineers, including those specializing in neural engineering, as many companies offer remote positions that involve programming, data analysis, and model development. Successful remote AI engineers typically have strong communication skills, proficiency with tools like Python and TensorFlow, and a reliable internet connection. However, some roles may require on-site presence for hardware setup or collaboration, depending on the company's policies.
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Remote Neural Engineer jobs near you

Machine Learning Research Scientist (Remote)

Moody's Analytics

New York, NY • On-site, Remote

Full-time

Posted 5 days ago

Job description

In the Predictive Analytics AI group, we build data-driven, highly distributed machine learning systems. Our engineers and researchers are responsible for architecting and developing these ML services end-to-end overcoming unique challenges that involve building systems that have high throughput availability, consistency, and low latency. The Predictive Analytics AI Group is the central group in Moody's Analytics comprising of researchers and engineers working together to build data-driven customer-facing products, as well as the necessary infrastructure to support the ML services following the industry leading practices. The group has worked on and built some award-winning AI products like Compliance Catalyst, Adverse Media Monitoring, Coronapulse, Quiqspread, News Edge 2.0, ESG and has participated in various internal automation initiatives. The group also regularly publish and present their work in top-tier academic and industry conferences. We have a flexible work environment and allow remote work depending on one's personal choice. 

Broadly, we are looking for colleagues who are passionate about: 

  • Natural language processing 
  • Information retrieval 
  • Information extraction 
  • Graph Neural Networks 
  • Recommender systems 
  • Knowledge graphs 
  • Explainable AI 

 

We'll trust you to: 
 

  • Collaborate with colleagues on production systems and applications 
  • Design, experiment, and evaluate algorithms as well as models using PyTorch, scikit-learn, Tensorflow, HuggingFace 
  • Work on POCs and research prototypes 
  • Provide thought leadership in machine learning 
  • Represent Moody's Analytics at scientific and industry conferences 
  • Lead collaboration with colleagues and academia to publish research findings in leading academic venues such as ACL, EMNLP, NAACL-HLT, AAAI, KDD, CIKM, SIGIR, ECIR 
     

You'll need to have: 

  • Ph.D. in CS, ML, Math, Statistics, Engineering, Quant, or relevant industry experience. 
  • Publication record in top-tier academic conferences and journals 
  • Proficiency in modern programming languages such as Python 
  • Proficiency in leading research projects 

Nice to have: 

  • Experience with MLOPs technologies and workflows 
  • Experience in working with engineering teams on taking research prototypes to production
Employment Type: FULL_TIME

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