Jobs → Engineering → Staff ML Engineer

About the Role We are looking for an experienced Staff ML Engineer with strong expertise in Machine Learning and the Semiconductor domain to work across the full stack — from AI models to silicon. This role involves optimizing AI training and inference, working with GPUs and AI accelerators, and adapting ML models and inference engines to real-world chip and NPU constraints. Key Responsibilities • Optimize ML training and inference across GPU and AI-accelerator infrastructure. • Design, train, evaluate, and deploy ML/DL, LLM, Computer Vision, and recommendation models. • Develop and optimize NPU cores and AI accelerator solutions for production silicon. • Build and optimize inference engines for latency, memory, and power efficiency. • Work with embedded Linux, BMC firmware, and RTOS environments such as Zephyr. • Develop automated testing and verification frameworks for AI-assisted RTL/DV and hardware bring-up. • Apply AI/ML techniques to hardware security, firmware security, and intrusion detection. • Collaborate with RTL, hardware, firmware, and QA teams to deliver end-to-end AI solutions. Requirements • Master’s degree or PhD is mandatory. • Strong experience in the Semiconductor domain. • Hands-on expertise in ML model development and optimization. • Experience with GPU/AI accelerator infrastructure and inference optimization. • Understanding of hardware–software co-design, embedded systems, or NPU architecture.