Sr. Staff Edge AI Applied Machine Learning Engineer

Reposted 22 Days Ago
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Austin, TX, USA
In-Office
Senior level
Hardware • Internet of Things • Software • Wearables • Semiconductor
Enabling all battery-powered mobile and portable IoT endpoint devices to be intelligent and energy-efficient.
The Role
Design, train, optimize, and deploy efficient on-device ML models (audio and vision) for resource-constrained products; maintain Ambiq ADKs; port and optimize customer models; apply model-efficiency techniques; produce customer-facing demos, docs, and benchmarks.
Summary Generated by Built In
Company Overview 

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 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.

Responsibilities 
  • 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.
Qualifications 
  • 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 You Need 

We're seeking passionate technologists who thrive on pushing boundaries, solving complex challenges, and driving transformative solutions. 

At Ambiqyou'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

C++
Compression
Docker
Executorch
Fft
Jax
Keras
Linux
Litert
Onnx
Pruning
Ptq
Python
PyTorch
Qat
Quantization
Rust
Sparsification
TensorFlow
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The Company
Austin, Texas
220 Employees
Year Founded: 2010

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

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