Junior System Modeling

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About this role

Junior System Modeling Palo Alto, CA I US Remote About Unconventional AI We are rethinking the foundations of the computer to optimize energy efficiency for AI. Founded by pioneers in the field - including Naveen Rao (Nervana, MosaicML) and Michael Carbin (MIT, MosaicML) - we are building a new computational substrate that interfaces directly with the physics of silicon to achieve biology-scale efficiency. We recently raised $475M in seed funding to turn this vision into reality. As a Junior Member of Technical Staff, System Modeling , you will work closely with senior engineers to contribute to the development of our multi-disciplinary simulation frameworks. You will assist the hands-on R&D team in building simulation environments that enable rapid iteration and testing across all layers of our unconventional physics-based computing systems for machine learning workloads. Your work will focus on integrating physics-based models, developing GPU-accelerated simulations, and supporting the cross-layer system integration necessary for "Extreme co-design". Key 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

Read the full description at unconv.ai. FewerJobs shows a source-linked preview and links to the original posting.