Ambiq designs and sells fabless semiconductors optimized for power-constrained edge AI workloads—wearables, smart home, industrial, and healthcare devices. The company has powered over 270 million devices to date. Technical hiring is accelerating (24 engineering roles posted in the last 30 days), with a strong skew toward senior and staff-level positions, indicating active architecture and optimization work rather than scaling to volume production. The project pipeline centers on Apollo SoC variants, secure bootloader implementation, and low-power MCU architecture—a tight focus on silicon tuning and design-in support.
Ambiq, founded in 2010 and headquartered in Austin, Texas, develops and licenses ultra-low-power semiconductor IP and reference designs built on patented subthreshold power optimization technology (SPOT). The company operates as a fabless semiconductor vendor, partnering with foundries and customers to deploy AI inference on battery-operated and energy-constrained devices. Primary verticals include wearables, smart buildings, industrial IoT, and medical devices. Ambiq sells both to device OEMs pursuing design wins and to ecosystem partners developing reference implementations and software stacks (Zephyr, FreeRTOS, ARM Cortex-M). The organization is 201–500 employees, engineering-heavy, with embedded software and hardware validation teams concentrated in the United States and Singapore.
Ambiq designs ultra-low-power microcontroller and SoC IP (Apollo family) optimized for edge AI. Products target wearables, smart home, industrial, and healthcare applications. The company has powered over 270 million devices with its subthreshold power optimization technology (SPOT).
Core stack: ARM Cortex-M, FreeRTOS, Zephyr, Keil, Synopsys PrimeTime, Verilog, SystemVerilog, UVM, JTAG, Bluetooth, Zigbee. Languages: C/C++, Python, Assembly, Perl. Ambiq is actively adopting Zephyr and FreeRTOS for embedded firmware.
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Ambiq's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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