Machine Learning Engineer
The Embedded Machine Learning Engineer (MLE) will drive the development of extreme low power machine learning (ML) networks for the lowest power processor on the planet. Responsibilities include understanding the applicability of machine learning (ML) networks for low power applications and proposing optimal implementations (software implementations and hardware acceleration). The MLE will develop and propose network and hardware architectures to realize incredible power savings without sacrificing performance using Ambiq’s SPOT technology. Working with 3rd party IP providers as well as developing internal solutions, the networks will be used in applications showcasing the advantages of Ambiq’s ultra-low power technology. The role involves selecting networks, training networks using industry leading ML development environments, integrating networks into common ML frameworks for demos, and understanding tradeoffs for complexity versus performance. Neural networks (NNs) will need to be right-sized per platform and endpoint compute application with difficult battery life and resource constraints. Application spaces will include far to near field audio, biometrics, sensor fusion, industrial, and a variety of always-on, multi-modal contextual awareness applications.
This role will involve significant engineering work in Ambiq’s R&D Center, but will also involve extensive partner and customer collaboration. The MLE will work closely and collaborate with thought leaders developing best-in-class IP to create innovative solutions for extremely challenging applications. The MLE is expected to work independently given high level goals and charters. This position will be part of the CTO’s Advanced Development Team.
- Review customer system/software/hardware design requirements to understand current and future challenges.
- Explore and understand new technology trends.
- Establish and maintain relationships with key software/hardware technology partners.
- Develop proprietary NNs or identify appropriate third party or open-source algorithms.
- Understand the tradeoffs per NN topology, per accuracy, per hardware architecture.
- Work within available ML development environments and frameworks.
- Propose hardware acceleration for energy optimization.
- Write white papers and feasibility studies to showcase the ultra-low power advantage provided by Ambiq’s products.
- Evangelize emerging technology and train/enable the sales team to win sockets.
The MLE should be an engineer or researcher with experience developing algorithms or NNs on embedded systems for endpoint AI applications. The MLE should additionally have experience collaborating with internal and external teams and presenting complex technical topics. The ideal candidate will have experience developing NNs for resource constrained, battery-powered applications. Experience with signal processing of a variety of signal types (sound, vibration, imaging, biometric, machine, etc.) is desirable. Experience with hardware architectures for NN acceleration and a familiarity with system and SoC design is extremely desirable.
- 2+ years’ experience in machine learning, applied math, or algorithm development, preferably in embedded applications.
- Experience with embedded Machine Learning applications (sound, speech, motion, and image classification) are highly desirable.
- Experience with common ML development frameworks highly desirable.
- Experience with embedded audio applications (hearables, voice assistants) is highly desirable.
- Experience with embedded biometric applications (fitness and medical devices) is highly desirable.
- Experience with embedded industrial IoT applications is highly desirable.
- Experience with multi-modal, contextual awareness applications is highly desirable.
- Experience designing embedded software for both MCUs as well as DSPs is valuable.
- Experience producing research papers, application notes, or white papers for a technical audience is highly desirable.
Key Personal and Professional Attributes:
Ambiq management has built a company that values continued technology innovation, a fanatical attention to customer needs, collaborative decision making, and, above all, enthusiasm for energy efficiency. The incoming MLE should embrace these same values. The MLE should have technical curiosity, passionate enthusiasm for innovating in challenging spaces, and a desire for a bureaucracy free environment. The MLE must also be extremely creative, innovating with existing products and planning for innovation in the next generation of products. The ideal MLE candidate will be hungry for success and will be ready to adapt and grow rapidly with Ambiq in the coming years.
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Machine Learning Engineer
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