Junior System Modeling

Unconventional AI is rethinking the foundations of computing to optimize energy efficiency for AI, having raised $475M in seed funding. They are seeking a Junior Member of Technical Staff in System Modeling to assist in the development of multi-disciplinary simulation frameworks and work on integrating physics-based models for machine learning workloads.

Responsibilities:

• Contribute to the implementation and optimization of GPU-accelerated simulators for ML on analog/unconventional hardware, focusing on specific modules and features within PyTorch
• Assist in integrating physics-based device and system models into the PyTorch simulation environment to help expose early algorithm–hardware tradeoffs and enable cross-layer optimization
• Support the maintenance and extension of the unified end-to-end simulation environment, helping to link theory, algorithms, and device models, and ensuring alignment between high-level and near-physical simulators
• Help implement and adhere to robust experiment tracking protocols to ensure simulation results, configurations, and non-idealities are reproducible and auditable
• Collaborate with Algorithms and Hardware teams to gather requirements and ensure the modeling environment meets their needs for high-level algorithm development and lower-level hardware verification