About Ai Engineering
Analog devices are a global leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge.
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.
Our company has revenue of more than $9 billion and approximately 24,000 people globally.
Our mission is to ensure today's innovators stay Ahead of What's Possible.
The Edge Ai Team is looking for a skilled Ai Engineer with a strong DSP background to work on projects that bridge digital signal processing and artificial intelligence.
This role focuses on developing Ai Models that integrate DSP pipelines with neural networks.
Your advanced expertise will play a critical role in advancing our Ai Technologies for deployment on hardware platforms.
Key Responsibilities:
Design and optimize Ai Architectures that effectively integrate DSP pipelines with neural networks.
Participate in all phases of ultra-applied projects, from ideation through to production.
Collaborate with cross-functional teams to implement Ai Solutions tailored for various applications.
Prototype and evaluate machine learning models to meet specific performance and application requirements.
Stay up to date with advancements in Ai and DSP Research and share insights with the team.
Qualifications:
A master's degree or equivalent experience.
5+ years of industry experience in Ai Machine Learning, or related areas, with a focus on DSP applications.
Demonstrated track record of working on machine learning models in production settings.
Strong understanding of digital signal processing and its application to Ai Models.
Strong understanding of neural networks (e.g., transformers, multimodal models, etc.).
Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and model optimization techniques.
Ability to work collaboratively with multidisciplinary teams and communicate technical concepts effectively.