Total Comp: Equity (Stock Options), Bonus Plan, Health Insurance, and more A pioneering AI semiconductor company is building a fundamentally current processing architecture designed to deliver dramatically lower power AI inferencing for always on, edge and endpoint devices. Their proprietary approach breaks from conventional digital compute, enabling real time processing of audio, vision, and sensor data at a fraction of the energy cost of traditional processors, unlocking current possibilities across smart devices, robotics, automotive, and wearable technology. With proven silicon already validated by customers and fresh investment behind them, they are now scaling their platform software team and are looking for a Senior ML Compiler Engineer to help take their technology from validation into high volume production.
Building and optimizing compilers to map deep neural networks onto a novel,
heterogeneous processing architecture Taking machine learning models and neural networks and efficiently fitting them onto unconventional compute arrays Collaborating with hardware and ML teams to co optimize model performance against silicon constraints Applying compiler design principles to non traditional computer architectures (FPGA, analog, neuromorphic) Contributing to a small, highly selective engineering team building category defining technology from the ground up 5+ years experience in compiler engineering, ideally within ML or deep learning contexts Experience with FPGA, analog, or neuromorphic computer architectures is highly valued Proven ability to take neural network models and translate them onto novel hardware targets This is a rare prospect to join a small, highly selective team working on technology built from first principles to redefine how machine learning is processed at the edge. Full details on the company will be shared once you're through to the next stage.