Company Overview
Ambiq is on a mission to enable intelligence everywhere — powering the AI edge revolution with the world's lowest-power semiconductor solutions.
Built on our proprietary sub- and near-threshold technology, our chips deliver multi-fold improvements in energy efficiency without costly process scaling. Since 2010, we've shipped over 290 million units to customers building smarter wearables, medical devices, IoT products, and AI-powered edge applications.
Our cross-functional teams span design, research, development, production, marketing, sales, and operations across Austin, Hsinchu, Shanghai, Shenzhen, and Singapore. We move fast, tackle hard problems, and create space for people to grow through complex, meaningful work that shapes the future of technology.
We're looking for self-motivated, creative problem-solvers who are eager to push technological limits and make a real impact in energy efficiency.
At Ambiq, we live by five values: Innovate. Collaborate. Focus. Learn. Achieve.
If that's you, join us — the intelligence everywhere revolution starts here.
Scope
Ambiq is seeking an Edge AI Firmware 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.
Skills Required
- BS in Electrical/Computer Engineering, Computer Science, or related field + 5+ years relevant experience (or equivalent practical experience)
- Designing, developing, and testing embedded software in C/C++
- Strong debugging discipline with emphasis on correctness, reproducibility, and preventing performance regressions
- Solid understanding of compute, memory, bandwidth/cache effects on latency and energy in constrained systems
- Ability to interpret hardware/software documentation (datasheets, reference manuals)
- Proficiency with Git (or equivalent version control)
- Efficient use of AI-assisted development tools while maintaining engineering rigor
- Experience with embedded development workflows: Arm toolchains, GDB + J-Link/SEGGER-class probes, and CMake/Make build systems
- Develop and support embedded AI runtimes and implement/optimize ML operator kernels for on-chip acceleration
Ambiq Compensation & Benefits Highlights
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Healthcare Strength — Health coverage is characterized as strong, with medical, dental, and vision included and plan quality described favorably. Additional supports such as FSA and related wellness-oriented perks are referenced, reinforcing overall healthcare breadth.
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Fair & Transparent Compensation — Pay is considered decent-to-good and roughly market-aligned overall, with certain roles described as competitive within the market. Total rewards span base, bonus, and equity, supporting a perception of balanced compensation.
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Leave & Time Off Breadth — Paid time off is part of the core package and generous parental leave is referenced by external profiles. Together these elements indicate a reasonably comprehensive time-off offering.
Ambiq Insights
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
Ambiq Offices
OnSite Workspace
Building silicon and embedded AI systems requires tight collaboration across firmware, hardware, validation, and architecture teams. We believe the hardest engineering problems are solved through direct, daily collaboration.
