Sr. Staff Edge AI Applied Machine Learning Engineer

Ambiq is seeking an experienced Edge AI Applied ML Engineer with deep experience in audio and computer vision. In this role you will design train optimize and deploy highly efficient on-device AI models—from ultra-small (tens of KB) to larger (hundreds of MB) footprints—targeting resource-constrained real-time battery-powered 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 will help 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 also help evolve our award-winning open-source AI Development Kits (ADKs): modular tooling that enables developers to mix-and-match datasets model architectures tasks training recipes and deployment targets. You will bridge cutting-edge research and practical productization by building production-grade demos reference applications and customer-facing tooling that accelerates real-world adoption.

• Develop and optimize on-device ML models for constrained real-time battery-powered products balancing accuracy with latency memory and energy.
• Build and maintain Ambiq’s open-source ADKs for modular datasets models tasks and training recipes.
• Translate cutting-edge research into production-grade demos and reference implementations.
• Apply model efficiency techniques: quantization compression pruning and structured sparsification.
• Serve as a domain expert in audio and vision (data strategy evaluation and failure analysis).
• Port and optimize customer models to Ambiq edge runtimes ensuring correctness performance and usability.
• Deliver and promote customer-ready assets: docs tutorials examples benchmarks plus white papers and conference representation.

• BS in Computer Science or related field + 5+ years of relevant experience (or equivalent practical experience). MS or PhD in related disciplines (ML EE signal processing computer vision robotics) is highly desirable.Strong proficiency in Python; working proficiency in C/C++ and/or Rust for performance and runtime integration.
• Domain expertise in audio (KWS speech enhancement SLM TTS) and/or vision (classify/detect/segment/pose/OBB/track) with DSP fundamentals (e.g. FFT).
• Comfortable in Linux development with Docker/dev containers (able to work across Mac/Windows as needed).
• Experience with one or more training frameworks: PyTorch TensorFlow JAX Keras.
• Strong ML engineering fundamentals: data pipelines augmentation metrics experiment reproducibility and failure analysis.
• Familiarity with edge deployment stacks such as ONNX LiteRT ExecuTorch.
• Hands-on with edge optimization: quantization (PTQ/QAT) compression and (structured) sparsification plus profiling for latency/memory/energy tradeoffs.
• Efficient use of AI-assisted development tools while maintaining rigor (testing review reproducibility).

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.

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 devicesModels optimized to run in tens of KBExtreme power efficiency for battery-operated systemsDeep hardware/software co-designThis is not research. It’s deployed technology.

Why Work With Us

Direct influence on silicon architectureSmaller high-impact teamsHardware/software co-design in real timeFaster technical decision cyclesVisible ownership at Staff & Director levelAustin-based collaboration culture