AI Algorithms/Software Engineer

Mythic

89d

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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.

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.
• 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.

What This Job Offers

• Education Level: Bachelor's degree
• Number of Employees: 11-50 employees