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Neural Networks Jobs (NOW HIRING)

Mythic

AI Algorithms/Software Engineer

Palo Alto, CA

$114.60K - $156.90K/yr

Builds software pipelines that adapt neural networks (such as Hugging Face, Ultralytics, or custom models) for deployment on Mythic's hardware. * Develops advanced quantization-aware and analog-aware ...

Mythic

AI Algorithms/Software Engineer

Austin, TX · Remote

$99.80K - $136.60K/yr

Builds software pipelines that adapt neural networks (such as Hugging Face, Ultralytics, or custom models) for deployment on Mythic's hardware. * Develops advanced quantization-aware and analog-aware ...

Mythic

AI Algorithms/Software Engineer

Palo Alto, CA

$114.60K - $156.90K/yr

Builds software pipelines that adapt neural networks (such as Hugging Face, Ultralytics, or custom models) for deployment on Mythic's hardware. * Develops advanced quantization-aware and analog-aware ...

Mythic

AI Algorithms/Software Engineer

Palo Alto, CA · Remote

$99.80K - $136.60K/yr

Builds software pipelines that adapt neural networks (such as Hugging Face, Ultralytics, or custom models) for deployment on Mythic's hardware. * Develops advanced quantization-aware and analog-aware ...

Mythic

AI Algorithms/Software Engineer

Austin, TX

$96.60K - $132.30K/yr

Builds software pipelines that adapt neural networks (such as Hugging Face, Ultralytics, or custom models) for deployment on Mythic's hardware. * Develops advanced quantization-aware and analog-aware ...

Mythic

AI Algorithms/Software Engineer

Austin, TX

$96.60K - $132.30K/yr

Builds software pipelines that adapt neural networks (such as Hugging Face, Ultralytics, or custom models) for deployment on Mythic's hardware. * Develops advanced quantization-aware and analog-aware ...

R3 Tek

Data Scientist

Bentonville, AR · On-site

Should be proficient with Artificial Neural Networks, Random forest. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and ...

Apple

ML Researcher, Autonomous Security

Austin, TX · On-site

You will be responsible for developing and evaluating iterative embedding techniques using sequential neural networks (e.g., RNNs, GRUs) that can process entire provenance graphs while consuming a ...

SpaceX

Software Engineer, Simulation

Hawthorne, CA · On-site

... neural networks--to accelerate simulations, enhance efficiency, drive novel improvements, increase part yield, reduce inspection burden, and optimize parts. • Collaborate with cross-functional ...

Apex Informatics

Data Scientist

Pleasanton, CA · On-site

Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages drawbacks. Knowledge of advanced ...

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How much do neural networks jobs pay per year?

As of May 29, 2026, the average yearly pay for neural networks in the United States is $132,391.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $168,000.00 per year, depending on experience, location, and employer.

What is a Neural Networks job?

A Neural Networks job typically involves designing, developing, and optimizing artificial neural networks for tasks such as image recognition, natural language processing, and predictive analytics. Professionals in this field work with machine learning frameworks like TensorFlow or PyTorch, train deep learning models, and fine-tune architectures for better accuracy and efficiency. These roles are common in AI research, data science, robotics, and software development. Strong skills in programming, mathematics, and data handling are essential for success in this field.

What are the key skills and qualifications needed to thrive in the Neural Networks position, and why are they important?

To thrive in a Neural Networks role, you need a solid background in mathematics, programming (Python, TensorFlow, PyTorch), and machine learning principles, often attained through a degree in computer science or a related field. Familiarity with neural network frameworks, model deployment tools, and cloud computing platforms is highly valuable, as are certifications such as TensorFlow Developer or AWS Machine Learning. Excellent problem-solving abilities, communication skills, and a collaborative mindset help you excel when working on interdisciplinary teams and complex projects. These skills are crucial for designing, training, and optimizing neural network models that effectively solve real-world problems in diverse industries.

What are the most common challenges faced in a Neural Networks role, and how can I prepare for them?

Professionals working in neural networks frequently encounter challenges such as managing large datasets, tuning hyperparameters, handling overfitting or underfitting, and keeping up with rapidly evolving technologies. You can prepare by building a strong foundation in relevant mathematical concepts, staying up-to-date on industry advancements, and practicing hands-on model development and troubleshooting. Collaborating with peers and participating in open-source projects or competitions can deepen your expertise and problem-solving skills. Employers also value candidates who can communicate complex ideas clearly and work well in diverse, multidisciplinary teams.
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Neural Networks jobs near you
Infographic showing various Neural Networks job openings in the United States as of May 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 73% In-person, and 27% Remote job distribution, with an average salary of $132,391 per year, or $63.6 per hour.
AI Algorithms/Software Engineer

AI Algorithms/Software Engineer

Mythic

Palo Alto, CA

$114.60K - $156.90K/yr

Full-time

Posted yesterday

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.
The AI Engineering team
  • Builds software pipelines that adapt neural networks (such as Hugging Face, Ultralytics, or custom models) for deployment on Mythic's hardware.
  • Develops advanced quantization-aware and analog-aware retraining algorithms leveraging PyTorch and ONNX.
  • Hardens networks to analog effects via advanced network regularization.
  • Models analog effects and their impact on network performance.
  • Works cross-functionally to validate and debug hardware.
  • Contributes to the co-design of next-generation hardware.
  • Brings up and customizes neural networks.
Here's what you will do
  • Optimize Mythic's analog-aware software toolchain for network accuracy, latency, and ease-of-use.
  • Design algorithms and tools for Mythic's neural network conversion pipeline.
  • Build high-fidelity, computationally-efficient hardware models.
  • Contribute to silicon bring-up, debugging, and validation.
  • Improve software through refactoring, testing, documentation, and other engineering best practices.
  • Stay current with advances in deep learning research and neural network frameworks.
Here's the background you need to have
  • Bachelor's degree in Computer Science, Mathematics, or a related field.
  • 5+ years of software experience in a production environment.
  • Experience working on complex problems with algorithm-heavy code.
  • Commitment to quality and engineering excellence.
  • Strong communication skills.
The following would be nice to have
  • MS/PhD in Computer Science, Mathematics, or related field.
  • Hands-on experience with modern neural network frameworks.
  • Familiarity with state-of-the-art neural network architectures.
  • Experience training neural networks with hardware-aware techniques, including quantization, pruning, or model-size limitations.
  • Experience with MLOps practices, including model versioning, CI/CD pipelines for ML, model deployment, and monitoring.
  • Experience owning critical APIs with a large user base.
  • Contributions to open-source software.
At Mythic, we foster a collaborative and respectful environment where people can do their best work. We hire smart, capable individuals, provide the tools and support they need, and trust them to deliver. Our team brings a wide range of experiences and perspectives, which we see as a strength in solving hard problems together. We value professionalism, creativity, and integrity, and strive to make Mythic a place where every employee feels they belong and can contribute meaningfully.
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