Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) PhD degree in Computer Science, Computer Engineering, or a related field Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience with ML frameworks (e.g., PyTorch) and the full software stack from model training/inference down to hardware execution Track record of technical leadership: defining roadmaps, driving cross-team alignment, and mentoring engineers Published research at top venues (ISCA, MICRO, HPCA, ASPLOS, MLSys) or equivalent industry contributions Experience with end-to-end AI hardware systems or on-device algorithm, logic and architecture development with performance, power and area optimizations Experience with numerics optimization (quantization, mixed-precision, custom number formats) for ML inference/training
$183,997/year to $257,000/year + bonus + equity + benefits
