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Core AI Developer

1 week ago

Limerick, Limerick, Ireland Analog Devices Full time

About Analog Devices

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Analog Devices is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge.

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We combine analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world.

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The AI Incubation team is looking for an experienced engineer to develop core AI technologies for our future Signal Chain AI products.

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Responsibilities

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We are seeking someone who can participate in all phases of our applied research projects in machine learning enabled DSP, from ideation through to production.

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This includes creating sandbox simulations, deployable implementations, and evaluation frameworks for algorithm performance and robustness.

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You will work with production coding counterparts to develop processes to transition successful proof-of-concept code.

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Additionally, you will stay up-to-date with the latest developments in machine learning and robotics from reputable groups.

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Qualifications

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To be successful in this role, you will need a Master's degree in electrical engineering, mechanical engineering, physics, computer science, robotics, or a related field; a Ph.D. is preferred.

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You should have 5 years of full-time industry experience and knowledge of digital signal processing, control theory, and its application with a focus on AI-enabled DSP.

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Strong proficiency in programming languages such as Python, Rust, C++ is also required.

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You will need a strong background in machine learning, deep neural networks, reinforcement learning, and other AI technologies.

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You must have excellent problem-solving skills and the ability to work collaboratively in an interdisciplinary team environment.

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A strong communication skillset, both written and verbal, is required.

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Preferred Qualifications

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We are looking for someone well-versed in concepts of audio signal processing (time & frequency domain processing, filtering, Fourier transform etc.).

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Knowledge of deep learning architectures for audio applications like audio enhancement, noise reduction, speech recognition, event detection/classification is also a plus.