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Neural Network Jobs (NOW HIRING)

Epsilon Systems Solutions

$121K - $167K/yr

Artificial neural network training * Programming: Python, C++, MATLAB, Go, PyTorch, TensorFlow, Keras * Image processing * Building graph databases * Building PostgreSQL databases with vector store ...

Urnet Inc

Engineer

Houston, TX · On-site

$100K - $150K/yr

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 ...

Nvidia

$54.50 - $72/hr

Enhance tool support to improve deep neural network design and performance efficiency. * Partner with management and architects to translate requirements into designs and own the development. * Stay ...

Avride

Machine Learning Engineer

Austin, TX · On-site

Required : • Strong understanding of fundamental machine learning algorithms and neural network techniques. • Expertise in at least one modern machine learning domain, such as computer vision ...

Avride

Machine Learning Engineer

Austin, TX · On-site

At least three years of experience developing neural network-based algorithms, including data collection, training, and deployment. * Proficiency in Python and ML frameworks such as PyTorch ...

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All JobsNeural Network Jobs

Neural Network information

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$22K

$106.6K

$162.5K

How much do neural network jobs pay per year?

As of Jul 7, 2026, the average yearly pay for neural network in the United States is $106,570.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,500.00 and $128,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Neural Network Engineer, you need a solid background in mathematics, machine learning theory, and programming, often backed by a degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience in data preprocessing, and knowledge of cloud computing platforms are typically required. Strong problem-solving abilities, collaboration, and effective communication skills distinguish top professionals in this role. These competencies are vital for developing, optimizing, and deploying neural network models that drive innovation in AI-powered solutions.

What is the difference between Neural Network vs Data Scientist?

AspectNeural NetworkData Scientist
Required CredentialsKnowledge of machine learning, programming skills, often a degree in computer science or related fieldsDegree in statistics, computer science, or related fields; strong analytical skills
Work EnvironmentResearch labs, tech companies, AI development teamsBusiness environments, consulting firms, research institutions
Industry UsageDeveloping AI models, deep learning applicationsData analysis, predictive modeling, business insights

Neural networks focus on building and training AI models using complex algorithms, while data scientists analyze data to extract insights and inform decisions. Both roles often collaborate but serve different functions within the AI and data analysis ecosystem.

What are neural networks?

Neural networks are a type of machine learning model inspired by the structure and function of the human brain. They consist of interconnected layers of nodes, or 'neurons,' that process data and learn to make predictions or decisions based on input data. Neural networks are widely used in applications such as image recognition, natural language processing, and autonomous systems. Their ability to learn complex patterns makes them powerful tools for solving problems that are difficult to program explicitly.

What are some common challenges neural network engineers face when deploying models to production environments?

Neural network engineers often encounter challenges such as model optimization for efficient inference, managing hardware constraints, and ensuring scalability during deployment. Addressing issues like latency, memory usage, and compatibility with production infrastructure is crucial, especially when models are resource-intensive. Collaborating closely with DevOps and software engineering teams is common to streamline deployment pipelines, monitor model performance, and quickly resolve issues that arise post-launch.
More about Neural Network jobs
What states have the most Neural Network jobs? States with the most job openings for Neural Network jobs include:
What job categories do people searching Neural Network jobs look for? The top searched job categories for Neural Network jobs are:
Neural Network jobs near you
Infographic showing various Neural Network job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, and 5% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $106,570 per year, or $51.2 per hour.
Postdoctoral Appointee: Neural Networks, Onsite

Postdoctoral Appointee: Neural Networks, Onsite

Sandia

Albuquerque, NM • On-site

$47K - $64K/yr

Full-time

Medical, Retirement, PTO

Posted 5 days ago

Job description

About Sandia
Sandia National Laboratories is the nation's premier science and engineering lab for national security and technology innovation, with teams of specialists focused on cutting-edge work in a broad array of areas. Some of the main reasons we love our jobs:
  • Challenging work with amazing impact that contributes to security, peace, and freedom worldwide
  • Extraordinary co-workers
  • Some of the best tools, equipment, and research facilities in the world
  • Career advancement and enrichment opportunities
  • Flexible work arrangements for many positions include 9/80 (work 80 hours every two weeks, with every other Friday off) and 4/10 (work 4 ten-hour days each week) compressed workweeks, part-time work, and telecommuting (a mix of onsite work and working from home)
  • Generous vacation, strong medical and other benefits, competitive 401k, learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance*

World-changing technologies. Life-changing careers. Learn more about Sandia at: http://www.sandia.gov
*These benefits vary by job classification.
What Your Job Will Be Like
We are seeking motivated postdoctoral candidates to advance the theory of brain-inspired algorithms and apply them to complex, real-world problems. The successful candidate will join an interdisciplinary team of computer scientists, mathematicians, engineers, and neuroscientists pursuing advanced research and development in neuromorphic computing, artificial intelligence, and spiking neural networks across a range of applications.
A strong background in theory (e.g., mathematics, theoretical neuroscience, computer science) is a necessity. Experience with artificial intelligence models or neural-inspired computing is strongly preferred.
On any given day, you may be called on to:
  • Develop and extend neural-inspired artificial intelligence algorithms;
  • Research theoretical principles and foundations necessary for model interpretability and introspection;
  • Program and test algorithms on neuromorphic and AI accelerator hardware;
  • Apply existing state-of-the-art methods and algorithms to domain data;
  • Engage with the community for conferences, workshops, proposals, and outreach;
  • Develop and support open-source research software packages;
  • Publish research results in high-quality journals and competitive conference venues.
    Due to the nature of the work, the selected applicant will be required to work onsite. Relocation provided for those who qualify.

Qualifications We Require
  • PhD in computer science, mathematics, theoretical neuroscience, physics, or a relevant field conferred within 5 years prior to start date.
  • Experience with theoretical or practical aspects of either neuromorphic algorithms or artificial intelligence.
  • Experience in a common programming language such as Python or C++.
  • Ability to obtain and maintain a DOE Q clearance.

Qualifications We Desire
  • Interest in developing neural-inspired and cutting-edge artificial intelligence algorithms (e.g., spiking neural networks, Bayesian neural networks, RNNs, LLMs) or in the deployment of such algorithms.
  • Experience with specialized computational architectures such as GPUs, FPGAs, neuromorphic processors, or machine learning accelerators.
  • Experience with neural network modeling languages (PyTorch,Tensorflow, Keras, etc.) or neural modeling languages.
  • Prior peer-reviewed research publications.
  • Demonstrated ability to work with others and contributed in a team environment.
  • Desire to work as part of a collaborative, multi-disciplinary team.
  • Willingness to be flexible in assignments and develop expertise in different areas of neuromorphic computing.

About Our Team
The department of Cognitive & Emerging Computing (Org. 01421) pursues foundational research and development of:
  • emerging general-purpose energy-efficient and beyond-Moore computing paradigms;
  • cognitive, brain-inspired and neuromorphic computing, human-machine interface technologies;
  • advanced heterogenous architectures based on integrated commodity components, special purpose accelerators, neural architectures and algorithms.

Posting Duration
This posting will be open for application submissions for a minimum of three (3) calendar days, including the 'posting date'. Sandia reserves the right to extend the posting date at any time.
Security Clearance
Sandia is required by DOE to conduct a pre-employment drug test and background review that includes checks of personal references, credit, law enforcement records, and employment/education verifications. Applicants for employment need to be able to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship. If you hold more than one citizenship (i.e., of the U.S. and another country), your ability to obtain a security clearance may be impacted.
Applicants offered employment with Sandia are subject to a federal background investigation to meet the requirements for access to classified information or matter if the duties of the position require a DOE security clearance. Substance abuse or illegal drug use, falsification of information, criminal activity, serious misconduct or other indicators of untrustworthiness can cause a clearance to be denied or terminated by DOE, resulting in the inability to perform the duties assigned and subsequent termination of employment.
EEO
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status and any other protected class under state or federal law.
NNSA Requirements for MedPEDs
If you have a Medical Portable Electronic Device (MedPED), such as a pacemaker, defibrillator, drug-releasing pump, hearing aids, or diagnostic equipment and other equipment for measuring, monitoring, and recording body functions such as heartbeat and brain waves, if employed by Sandia National Laboratories you may be required to comply with NNSA security requirements for MedPEDs.
If you have a MedPED and you are selected for an on-site interview at Sandia National Laboratories, there may be additional steps necessary to ensure compliance with NNSA security requirements prior to the interview date.
Position Information
This postdoctoral position is a temporary position for up to one year, which may be renewed at Sandia's discretion up to five additional years. The PhD must have been conferred within five years prior to employment.
Individuals in postdoctoral positions may bid on regular Sandia positions as internal candidates, and in some cases may be converted to regular career positions during their term if warranted by ongoing operational needs, continuing availability of funds, and satisfactory job performance.

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