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Neural Network Jobs (NOW HIRING)

Cmu

RF Cyber Lab Intern

Pittsburgh, PA · On-site

$14.50 - $19.50/hr

Position Summary: We seek an intern with knowledge of temporal neural network design as well as the fundamentals of digital signal processing to help develop and refine novel detection and ...

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 ...

Avride

Senior / Staff Machine Learning Engineer

Austin, TX · On-site

$124K - $171K/yr

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

femtoAI

Hardware Engineer

San Bruno, CA · On-site

$147K - $194K/yr

As a Hardware Engineer, you will join femtoAI's hardware team to help design and build our novel neural network accelerator. Working in a small, highly collaborative group, you will contribute ...

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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.
RF Cyber Lab Intern

RF Cyber Lab Intern

Software Engineering Institute

Pittsburgh, PA • On-site

$14.50 - $19.50/hr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

What We Do: The SEI helps advance software engineering principles and practices and serves as a national resource in software engineering, computer security, and process improvement. The SEI works closely with defense and government organizations, industry, and academia to continually improve software-intensive systems. Our core purpose is to help organizations improve software engineering capabilities and develop or acquire the right software, defect free, within budget and on time, every time. The core purpose here isn't helping someone achieve software process nirvana though - we want highly resilient RF communications in contested environments.
Position Summary: We seek an intern with knowledge of temporal neural network design as well as the fundamentals of digital signal processing to help develop and refine novel detection and classification techniques of RF signals across various architectures.
Requirements:
  • Enrolled in a masters or other post-graduate program
  • Have a bachelors in electrical or computer engineering
  • Previously taken or enrolled in CMU 18-743 or equivalent
  • Engagement with CMU-NCA Lab
  • Ability to work in a lab as needed on the CMU Pittsburgh campus
  • You will be subject to a background check and must be eligible to work in the United States without Visa sponsorship.

Knowledge, Skills and Abilities:
  • Signal processing fundamentals
  • Artificial neural networks design and implementation
  • Spiking temporal neural network implementation
  • Strong programming ability and analytical skills

Job Function Breakdown:
70% Development and analysis of RF signal detection and classification
20% Collection, preparation, collation of sample RF data for processing
10% Development of other signal processing algorithms and systems
TOTAL = 100%
Position in office 5 days a week.
Location
Pittsburgh, PA
Job Function
Non-CMU Students
Position Type
Intern (Fixed Term)
Full time/Part time
Full time
Pay Basis
HourlyMore Information:
  • Please visit "Why Carnegie Mellon" to learn more about becoming part of an institution inspiring innovations that change the world.
  • Click here to view a listing of employee benefits
  • Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.
  • Statement of Assurance

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