AI Algorithms/Software Engineer

Latent AI; Palo Alto (CA); On-site; USD 120,000 - 150,000; Full time

Job summary

Latent AI in Palo Alto is looking for an experienced AI Engineer to optimize software pipelines for neural network deployments on specialized hardware. You'll design algorithms and contribute to network accuracy while improving the software through best engineering practices. A Bachelor's degree in Computer Science or a related field and at least 5 years of relevant experience are required. Knowledge of PyTorch and ONNX is essential, along with strong communication skills.

Qualifications

• 5+ years of software experience in a production environment.
• Experience working on complex problems with algorithm-heavy code.
• Commitment to quality and engineering excellence.

Responsibilities

• 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.
• Contribute to silicon bring-up, debugging, and validation.

Skills

Software pipeline development

Neural network optimization

Algorithm design

Communication skills

Education

Bachelor's degree in Computer Science, Mathematics, or related field

Tools

PyTorch

ONNX

Job description

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.