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How much do neural network developer jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for neural network developer in the United States is $48.73, according to ZipRecruiter salary data. Most workers in this role earn between $36.78 and $62.50 per hour, depending on experience, location, and employer.

What is the difference between Neural Network Developer vs Machine Learning Engineer?

AspectNeural Network DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related fields; knowledge of neural networksBachelor's or Master's in CS, Data Science, or related fields; broader ML knowledge
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural network modelsTech companies, data-driven firms, AI teams working on various ML models
Employer & Industry UsagePrimarily in AI research, deep learning projects, and neural network applicationsAcross industries like finance, healthcare, and tech for diverse ML solutions

Neural Network Developers specialize in designing and implementing neural network architectures, focusing on deep learning models. Machine Learning Engineers have a broader scope, working on various ML algorithms beyond neural networks. Both roles require similar educational backgrounds but differ in focus and application areas.

What are popular job titles related to Neural Network Developer jobs?

For Neural Network Developer jobs, the most frequently searched job titles are:

Infographic showing various Neural Network Developer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 80% Full Time, 11% Part Time, and 7% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $101,366 per year, or $48.7 per hour.

Senior Systems Engineer - Signal Processing, Algorithms and Characterization

Austin, TX

Mythic
See more jobs at Mythicexternal

$150K - $275K/yr

Full-time

Re-posted 11 days ago

Job description

Mythic is building the future of AI computing with breakthrough analog technology that delivers 100 the performance of traditional digital systems at the same power and cost. This unlocks bigger, more capable models and faster, more responsive applications-whether in edge devices like drones, robotics, and sensors, or in cloud and data center environments. Our technology powers everything from large language models and CNNs to advanced signal processing, and is engineered to operate from -40 C to +125 C, making it ideal for industrial, automotive, aerospace, and defense. We've raised over $100M from world-class investors including Softbank, Threshold Ventures, Lux Capital, and DCVC, and secured multi-million-dollar customer contracts across multiple markets.

Mythic's analog compute hardware is a massive integration of analog and digital components on a single chip, with multiple cascaded digital and analog stages. The fundamental compute atomic is a vector-product that is entirely processed in the analog domain. So, analog impairments like ADC/DAC non-linearity and weight-noise directly impact the accuracy of the vector-multiply operation. Mitigation techniques for these impairments thus become critical and is the realm that the Systems Engineer operates in. Therefore, the Systems Engineer role maps directly onto skills from RF baseband, high-speed digital communication system design and RF sensing- think Wi-Fi, SerDes, gigabit Ethernet and sensor signal processing. 

The Systems Engineering team

  • Sits at the intersection of Analog, AI, Firmware and Silicon Productization,

  • Models analog effects and their impact on neural network performance.

  • Develops signal-processing based solutions to mitigate impact of analog impairments on neural network accuracy

  • Works cross-functionally to validate, debug, and optimize analog compute hardware.

  • Contributes to the design of next-generation hardware.

  • Brings up new silicon, characterizes silicon performance and develops effective approaches for silicon screening

  • Builds frameworks for large-scale data capture and statistical error analysis for analog compute in the simulation domain and on actual silicon hardware

Here's what you will do

  • Own various aspects of algorithms and DSP blocks that optimize the performance of Mythic's unique analog compute-in-memory technology from concept to customer deployment. This includes calibration loops, non-linearity compensation, offset-correction and estimation of residual-errors.

  • Work with model-training, compiler and firmware teams to productize these algorithms.

  • Write and modify firmware as needed to productize/debug algorithms

  • Continually improve on the fidelity of our modeling and simulation environment to better predict silicon performance.

  • Correlate errors seen on silicon to simulation models and contribute to improving the fidelity of our models for analog compute.

  • Develop Python frameworks for data collection, error-analysis and quantify impact of analog impairments on neural-network accuracy

  • Silicon bring-up, Characterization and Performance-Optimization.

Here's the background you need to have

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Mathematics, Physics or a related field.

  • At least 5 years experience in production DSP or RF baseband engineering (< 3 years if Ph.D or M.S.)

  • Strong familiarity with production Python coding, including object oriented and/or functional programming

  • Strong familiarity with core DSP concepts, including frequency domain analysis, filtering, statistical signal processing and estimation theory

  • Track record of shipping silicon with DSP or RF/Analog sub-systems. 

  • Understanding of linear algebra concepts, including matrix math and linear regression. 

  • Comfort with large-scale collection and processing of signals. 

  • Commitment to quality and engineering excellence.

  • Strong communication skills.

The following would be nice to have

  • MS/PhD in Electrical Engineering, Computer Science, Mathematics, Physics or related field.

  • Experience with RF calibration and silicon-bringup in the high-speed communication space

  • Strong familiarity with NumPy/SciPy (or experience with Numpy and strong familiarity with MATLAB for DSP).

  • Familiarity with state-of-the-art neural network architectures

$150,000 - $275,000 a year
Compensation is based on a variety of factors, including but not limited to: location, education, and years of experience.
At Mythic, we pride ourselves in creating a culture where all employees feel valued and appreciated for the diverse perspectives and backgrounds they bring to the team. We aim to hire smart people, give them the resources they need to do their job well, and then leave the rest up to them. We celebrate individual differences and encourage people to be comfortable bringing their authentic selves to work. At the end of the day, we are committed to building a diverse workforce where everyone belongs.

Mythic is an equal opportunity and affirmative action employer. It ensures equal employment opportunity without discrimination or harassment based on race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, disability, national origin, marital or domestic/civil partnership status, genetic information, citizenship status, veteran status, or any other characteristic protected by law.

We look forward to reviewing your application!
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