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Remote Neural Network Engineer Jobs in Raleigh, NC

First Citizens Bank

Network Engineer III

Raleigh, NC · On-site +1

$143K - $189K/yr

Overview May work remotely pursuant to First Citizens' Remote Work Guidelines policy. Provides ... Engineer, Network Specialist, Network Engineer, Network Analyst, Network Administrator, IT ...

First Citizens Bank

Network Engineer III

Raleigh, NC · On-site +1

$143K - $189K/yr

Overview May work remotely pursuant to First Citizens' Remote Work Guidelines policy. Provides ... Engineer, Network Specialist, Network Engineer, Network Analyst, Network Administrator, IT ...

SHI

Presales Solutions Engineer - Network

Durham, NC · On-site +1

Job Summary The Presales Solutions Engineer- Network will work alongside Architects as a network ... This position is remote in the Raleigh, NC area with a hybrid setup as determined by SHI management.

Varsity Tutors

Machine Learning Tutor

Chapel Hill, NC · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... neural network architectures while preparing students for data science roles and advanced AI ...

Varsity Tutors

Machine Learning Tutor

Durham, NC · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... neural network architectures while preparing students for data science roles and advanced AI ...

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All JobsNeural Network Engineer JobsRemote Neural Network Engineer JobsRemote Neural Network Engineer Jobs in Raleigh, NC

Remote Neural Network Engineer information

See Raleigh, NC salary details

$30.1K

$106K

$153.6K

How much do remote neural network engineer jobs pay per year?

As of Jun 18, 2026, the average yearly pay for remote neural network engineer in Raleigh, NC is $105,995.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,500.00 and $129,800.00 per year, depending on experience, location, and employer.

What is a Remote Neural Network Engineer?

A Remote Neural Network Engineer is a specialized software engineer who designs, develops, and maintains neural network models while working from a remote location. They use deep learning frameworks such as TensorFlow or PyTorch to build algorithms that mimic the human brain for tasks like image recognition, natural language processing, and predictive analytics. These engineers collaborate with teams virtually and leverage cloud computing resources to train and deploy models. The role requires strong programming, mathematical, and analytical skills, as well as experience working in distributed team environments.

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

AspectRemote Neural Network EngineerData Scientist
Required CredentialsBachelor's or Master's in Computer Science, AI, or related fields; experience with neural networks and deep learning frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentRemote, tech companies, AI research labsRemote or on-site, diverse industries including finance, healthcare, tech
Industry UsagePrimarily in AI, machine learning, and deep learning projectsData analysis, predictive modeling, business insights

While both roles involve working with data and machine learning, a Remote Neural Network Engineer specializes in designing and implementing neural network models, often requiring deep learning expertise. A Data Scientist focuses on analyzing data to extract insights, using a broader set of tools including statistical methods and machine learning. The roles overlap in skills but differ in focus and application.

What engineers make $500,000?

Senior neural network engineers with extensive experience, advanced skills in deep learning frameworks, and a strong track record in AI research can earn salaries around $500,000, especially in high-cost-of-living areas or at leading tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise in machine learning, data science, and software engineering.

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

To thrive as a Remote Neural Network Engineer, you need a strong background in computer science, mathematics, and deep learning principles, often supported by a relevant degree and prior experience in AI or machine learning roles. Proficiency in programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms are essential, and certifications in machine learning can be advantageous. Excellent problem-solving skills, self-motivation, and effective remote communication are key soft skills for collaboration and independent work. These skills and qualities ensure the engineer can design, implement, and optimize neural network solutions efficiently while contributing effectively to distributed teams.

Is ML a high paying job?

Machine Learning (ML) roles, including Neural Network Engineers, are generally high-paying due to the specialized skills required, such as programming in Python, experience with frameworks like TensorFlow or PyTorch, and knowledge of data science. Salaries tend to be above average in the tech industry, especially for those with advanced expertise and relevant certifications.

How does a Remote Neural Network Engineer typically collaborate with cross-functional teams when working from a distance?

As a Remote Neural Network Engineer, collaboration with cross-functional teams—such as data scientists, software engineers, and product managers—is primarily facilitated through virtual communication platforms and project management tools. Regular video meetings, code reviews, and shared documentation are essential to ensure alignment on project goals and progress. Clear communication and proactive sharing of updates are crucial to overcoming the lack of in-person interaction. Additionally, remote engineers often use collaborative coding environments and version control systems to streamline joint development efforts and maintain code quality.

What engineers make $300,000 a year?

Senior neural network engineers, especially those with expertise in deep learning, AI research, and experience with frameworks like TensorFlow or PyTorch, can earn $300,000 or more annually. High salaries are often associated with roles in leading tech companies, specialized skills, advanced degrees, and significant industry experience.

Which 5 jobs will survive AI?

Remote Neural Network Engineers are likely to continue in demand as AI advances because they develop and optimize AI models, requiring specialized skills in machine learning, programming, and data analysis. Jobs that involve complex problem-solving, creativity, and human interaction, such as healthcare professionals, educators, software developers, data scientists, and cybersecurity specialists, are also expected to persist despite AI automation. These roles often require critical thinking and adaptability that AI cannot fully replicate.
What are popular job titles related to Remote Neural Network Engineer jobs in Raleigh, NC? For Remote Neural Network Engineer jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Remote Neural Network Engineer jobs in Raleigh, NC look for? The top searched job categories for Remote Neural Network Engineer jobs in Raleigh, NC are:
Remote Neural Network Engineer jobs near you

Staff ML Scientist - Neuromorphic Computing & Spiking Neural Networks

Triangle Workforce

Durham, NC • Remote

Full-time

Posted 7 days ago

Job description

We are hiring a Staff ML Scientist to lead research and development of spiking neural network (SNN) architectures for ultra-low-power, real-time edge inference. This rare role sits at the convergence of computational neuroscience and production machine learning, requiring expertise in neuromorphic hardware platforms (Intel Loihi 2, BrainChip Akida, SynSense), temporal coding schemes, and spike-timing-dependent plasticity (STDP) learning rules.


You will design brain-inspired ML models that achieve orders-of-magnitude improvements in energy efficiency over traditional deep learning for time-series, sensor fusion, and event-driven vision applications.


Candidates must have hands-on experience training and deploying SNNs, deep familiarity with frameworks like Norse, snnTorch, or Lava, and ideally published work in neuromorphic engineering or computational neuroscience. PhD required. Experience bridging the gap between neuromorphic research prototypes and production-ready inference systems is critical.


Key Skills: Spiking Neural Networks, Neuromorphic Computing, Intel Loihi, snnTorch, Norse, Lava, Edge ML, Sensor Fusion, PyTorch, STDP


This is a remote-first position based in North Carolina.