Ambiq's mission is to enable intelligence everywhere by delivering the lowest power semiconductor solutions. Ambiq is a pioneer and a leading provider of ultra-low-power semiconductor solutions based on our proprietary and patented sub- and near-threshold technologies. With the increasing power requirements of artificial intelligence (AI) computing, our customers are relying on our solutions to deliver AI to edge environments. Our hardware and software innovations fundamentally deliver a multi-fold improvement in power consumption over traditional semiconductor designs without expensive process geometry scaling. We began in 2010 by addressing the power consumption challenges of battery-powered devices at the edge, where they were most pronounced. As of the beginning of 2025, we've shipped more than 280+ million units worldwide.
Our innovative and fast-moving teams of design, research, development, production, marketing, sales, and operations are spread across several continents, including the US (Austin), Taiwan (Hsinchu), China (Shanghai and Shenzhen), and Singapore. We value relentless technology innovation, a deep commitment to customer success, collaborative problem-solving, and an enthusiastic pursuit of energy efficiency. We embrace candidates who also share these same values. The successful candidate must be self-motivated, creative, and comfortable learning and driving exciting new technologies. We encourage and nurture an environment that fosters growth and opportunities to work on complex, meaningful, and challenging projects, creating a lasting impact and shaping the future of technology. Join us on our quest for enabling billions of intelligent devices. The intelligence everywhere revolution starts here.
Scope
Ambiq is seeking a Principal Edge AI Runtime & Compiler Engineer to build and optimize the embedded software stack that powers real-time, battery-powered on-device AI. You will develop Ambiq’s AI runtimes, performance-critical operator libraries, and profiling/debug tooling that enable customers to deploy efficient inference on resource-constrained devices.
While the cloud has been the default home for AI, the next frontier is distributing intelligence everywhere—directly onto real-world devices. Edge AI enables real-time responsiveness, stronger privacy, lower bandwidth cost, and reliable operation even without connectivity. This role helps accelerate the shift to on-device intelligence across a rapidly growing ecosystem of health and fitness wearables, smart glasses, industrial IoT, and always-on sensors.
You’ll work closely with platform, silicon, and applied ML teams—and directly with customers—to ensure our software extracts maximum performance and energy efficiency from Ambiq hardware while remaining easy to integrate into production embedded toolchains.
Responsibilities
- Develop and support Ambiq’s embedded AI runtimes (HeliaRT—our fork/extension of TensorFlow Lite for Microcontrollers—and HeliaAOT) with focus on portability, correctness, performance, and usability.
- Implement and optimize ML operator kernels and embedded libraries for on-chip acceleration (DSP, vector, NPU), including HeliaDSP and HeliaCore components.
- Build and maintain on-device profiling and performance analysis tools, including converting PMU counters into actionable insights.
- Drive improvements in latency, memory footprint, and energy (e.g., joules/inference) through compute/bandwidth and memory-hierarchy analysis.
- Develop benchmark harnesses, microbenchmarks, and regression tests to ensure numerical correctness and prevent performance regressions.
- Enable seamless customer integration across embedded environments and toolchains (bare metal, FreeRTOS, Zephyr).
- Improve memory planning/runtime efficiency and manage upstream/fork health; publish and maintain customer-facing assets (docs, guides, examples, benchmarks).
Qualifications
- BS in Electrical/Computer Engineering, Computer Science, or related field + 5+ years relevant experience (or equivalent practical experience). MS is a plus, especially in embedded systems, compilers, computer architecture, or ML systems.
- Strong experience designing, developing, and testing embedded software in C/C++.
- Strong debugging discipline with an emphasis on correctness, reproducibility, and performance regression prevention.
- Solid understanding of compute, memory, and bandwidth/cache effects on deterministic latency and energy efficiency in constrained systems.
- Ability to interpret hardware/software documentation (datasheets, reference manuals; schematics a plus).
- Proficiency with Git (or equivalent version control).
- Efficient use of AI-assisted development tools to improve productivity while maintaining engineering rigor.
- Experience with embedded development workflows: Arm toolchains, GDB + J-Link/SEGGER-class probes, and CMake/Make build systems.
Nice to have:
- Python for profiling/analysis tooling, automation, and developer utilities.
- Rust experience.
- Familiarity with TensorFlow Lite for Microcontrollers (or similar embedded inference runtimes).
- Experience optimizing for embedded acceleration targets (e.g., DSP, vector extensions, NPU).
- Familiarity with CMSIS-NN, CMSIS-DSP, and/or Vela (or similar).
- Working knowledge of quantized inference (e.g., int8, per-channel) and embedded debugging implications.
- Packaging/integration (e.g., CMSIS-Pack/CPM.cmake) and/or lab measurement experience (power/debug with basic bench tools).
Must be currently authorized to work in the United States for any employer. We do not sponsor or take over sponsorship of employment visas (now or in the future) for this role.
We're seeking passionate technologists who thrive on pushing boundaries, solving complex challenges, and driving transformative solutions.
At Ambiq, you'll collaborate with a dynamic team that values relentless innovation, customer-centric thinking, and continuous learning. If you're a self-motivated, creative problem-solver eager to push technological limits and make a meaningful impact in energy efficiency, this is your opportunity to grow, excel, and turn groundbreaking ideas into reality.
Most importantly, the successful candidate will be able to live the Ambiq Shared Values:
- Innovate: We tenaciously find ways to break down the barriers to possible solutions
- Collaborate: We proactively communicate and encourage each other to be better.
- Focus: We keep the voice of the customer at the center of everything we do.
- Learn: We strive for continuous improvement and are always curious.
- Achieve: We execute on quality and follow through on our commitments.
Top Skills
What We Do
Ambiq makes unprecedented energy-efficient SoCs and ultra-low power platform solutions that enable edge AI on billions of battery-powered devices. Our mission is to put intelligence everywhere by delivering the lowest-power semiconductor solutions on the planet. With SPOT® technology and the Apollo SoC family, Ambiq empowers innovators to build smarter, longer-lasting wearables, IoT, smart home, healthcare, and industrial devices. Ambiq has helped leading manufacturers worldwide develop products that last weeks on a single charge (rather than days) while delivering a maximum feature set in compact industrial designs. Ambiq's goal is to take Artificial Intelligence (AI) where it has never gone before in mobile and portable devices, using Ambiq's advanced ultra-low power system on chip (SoC) solutions. Ambiq has shipped more than 200 million units as of March 2023. The next generation of AI will not depend on constant cloud connectivity. It will run directly on ultra-low-power silicon in wearables, sensors, and embedded systems. At Ambiq, we design and ship production silicon that enables: Real-time inference on constrained devices Models optimized to run in tens of KB Extreme power efficiency for battery-operated systems Deep hardware/software co-design This is not research. It’s deployed technology.
Why Work With Us
Direct influence on silicon architecture Smaller, high-impact teams Hardware/software co-design in real time Faster technical decision cycles Visible ownership at Staff & Director level Austin-based collaboration culture
