Jobs → Engineering → Staff ML Engineer

About the Role We are looking for an experienced Staff ML Engineer with strong expertise in AI/ML, semiconductor technology, and hardware-aware machine learning to work across the full stack—from model development to AI silicon. Key Responsibilities • Optimize ML training and inference performance across GPUs and AI accelerators • Design, train, evaluate, and deploy ML models, including Deep Learning, LLMs, Computer Vision, and Recommendation Systems • Optimize inference engines and serving runtimes for hardware constraints such as latency, memory, and power • Work with NPU architectures, embedded systems, firmware, and hardware verification • Build automated testing and verification frameworks for AI-assisted hardware development • Apply AI/ML techniques to cybersecurity, intrusion detection, and firmware security • Collaborate with hardware, RTL, firmware, and QA teams to deliver end-to-end AI solutions Requirements • 5–7+ years of hands-on AI/ML engineering experience • Master’s degree mandatory; PhD preferred • Semiconductor domain experience is mandatory • Experience with GPU infrastructure, distributed training, inference optimization, and MLOps • Strong model development, evaluation, deployment, and data pipeline experience • Hands-on expertise in at least two of the following areas: NPU / AI accelerators, Embedded Linux, BMC firmware, or RTOS, Inference engines and serving runtimes, Hardware test and verification automation, AI-driven cybersecurity