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Neural Network Jobs (NOW HIRING)

Analyze neural network workloads and identify architectural enhancements required to improve performance, power efficiency, memory bandwidth utilization, and silicon area. * Define HW/SW partitioning ...

$179K/yr

WY-CY-7203 THE CYBERNETICS DIVISION IS SEEKING A SYNTHETIC SYSTEMS ARCHITECT TO LEAD THE DESIGN AND DEVELOPMENT OF NEXT-GENERATION NEURAL NETWORK ARCHITECTURES FOR OUR SYNTHETIC PERSON PLATFORM. THIS ...

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 ...

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 ...

Showing results 21-40

Neural Network information

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$22K

$106.6K

$162.5K

How much do neural network jobs pay per year?

As of Sep 10, 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 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 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 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.

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 is the main job of a neural network?

A neural network job involves designing, training, and optimizing artificial models that mimic the human brain's neural connections to recognize patterns, make predictions, or classify data. This role requires knowledge of machine learning, programming skills, and experience with tools like TensorFlow or PyTorch.
More about Neural Network jobs

What states have the most Neural Network jobs?

States with the most job openings for Neural Network jobs include:

Infographic showing various Neural Network job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 81% Full Time, 11% Part Time, and 6% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $106,570 per year, or $51.2 per hour.

Computer Vision System Engineer

San Diego, CA • On-site

Qualcomm
Technology, Communication and Media • 10K+ employees

Full-time

Posted 23 days ago


Key responsibilities

  • Study state-of-the-art computer vision and deep learning models and define efficient mappings onto mobile AI accelerators and heterogeneous compute platforms.

  • Drive architecture development for hardware-aware deep learning engines, including support for neural network operators, dataflows, tensor processing pipelines, quantization, and memory hierarchies.

  • Analyze neural network workloads and identify architectural enhancements to improve performance, power efficiency, memory bandwidth utilization, and silicon area.


Qualcomm rating

8.8

Company rating: 8.8 out of 10

Based on 11 frontline employees who took The Breakroom Quiz


Job description

Company:
Qualcomm Technologies, Inc.
Job Area:
Engineering Group, Engineering Group > Video Systems, HW Architecture
General Summary:
Qualcomm's computer vision system design Group is seeking candidates for its Mobile Computer Vision and AI Systems Architecture Team. The team develops next-generation mobile computer vision and deep learning solutions for imaging, perception, scene understanding, segmentation, tracking, computational photography, and AI-powered experiences.
We are seeking candidates with strong expertise in hardware-aware algorithm design, deep learning engine architecture, system architecture, HW/SW co-design, and accelerator development for mobile computer vision and AI workloads. The ideal candidate will possess deep knowledge of computer vision and neural network algorithms and practical experience translating them into power-efficient, real-time implementations on heterogeneous mobile platforms consisting of CPUs, GPUs, DSPs, NPUs, and dedicated AI accelerators. The candidate is expected to drive architecture definition for next-generation deep learning engines and computer vision accelerators, including compute, memory, dataflow, scheduling, quantization, and HW/SW partitioning strategies that maximize performance-per-watt.
Principal Duties and Responsibilities:
  • Study state-of-the-art computer vision and deep learning models and define efficient mappings onto mobile AI accelerators and heterogeneous compute platforms.
  • Drive architecture development for hardware-aware deep learning engines, including support for emerging neural network operators, dataflows, tensor processing pipelines, quantization techniques, and memory hierarchies.
  • Analyze neural network workloads and identify architectural enhancements required to improve performance, power efficiency, memory bandwidth utilization, and silicon area.
  • Define HW/SW partitioning strategies across CPUs, GPUs, DSPs, NPUs, and dedicated accelerators.
  • Develop workload characterization methodologies and performance models for computer vision and AI applications.
  • Collaborate with hardware architects and designers to define next-generation AI engine features and capabilities based on evolving computer vision workloads.
  • Drive top-down architecture exploration from algorithm requirements through hardware implementation, including performance, power, thermal, and area projections.

Minimum Qualifications:
• Bachelor's degree in Computer or Electrical Engineering, Computer Science, or related field and 2+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
OR
Master's degree in Computer or Electrical Engineering, Computer Science, or related field and 1+ year of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer or Electrical Engineering, Computer Science, or related field.
Preferred Qualifications
  • Multiple years of experience developing mobile computer vision and AI systems.
  • Deep knowledge of modern neural network architectures, including CNNs, Transformers, Vision Transformers (ViTs), multi-modal perception systems, and hardware-aware model optimization techniques.
  • Experience architecting and optimizing deep learning engines (DLEs) or AI accelerators for computer vision workloads.

Additional Requirements
  • Strong understanding of mobile computer vision applications, including: Object Detection and Tracking, Segmentation, Scene Understanding, Image Enhancement and Computational Photography, Motion Estimation and Neural Network-Based Vision Systems
  • Expertise in system architecture and HW/SW partitioning for computer vision and AI workloads.
  • Strong understanding of deep learning accelerator architectures, including Tensor processing, optimization, compute and neural network bottlenecks
  • Experience defining real-time hardware architectures for computer vision and deep learning workloads.
  • Experience evaluating throughput, latency, power, memory bandwidth, and silicon area trade-offs.
  • Strong programming skills in C/C++ and Python with hands-on experience in algorithm prototyping and performance analysis.

Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
Pay range and Other Compensation & Benefits:
$122,500.00 - $213,200.00
The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer - and you can review more details about our US benefits at this link.
If you would like more information about this role, please contact Qualcomm Careers.

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About Qualcomm

Sourced by ZipRecruiter

Qualcomm is enabling a world where everyone and everything can be intelligently connected. You interact with products and technologies made possible by Qualcomm every day, including 5G-enabled smartphones that double as pro-level cameras and gaming devices, smarter vehicles and cities, and the technology behind the smart, connected factories that manufactured your latest purchase. Our powerful connectivity solutions keep you connected—even in remote areas. Qualcomm 5G and AI innovations are the power behind the connected intelligent edge. You’ll find our technologies behind and inside the innovations that deliver significant value across multiple industries and to billions of people every day.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Diego, CA, US

Year founded

1985