Staff ML Engineer

Key Skills

Aartificial intelligence, Deep Learning, DevOps, Large Language Models - LLMs, Machine learning techniques, Mathematical modeling, Python Programming, Software Development

Job Description

Analog Devices, Inc. (NASDAQ: ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines 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. With revenue of more than $12 billion in FY22 and approximately 25,000 people globally working alongside 125,000 global customers, ADI ensures today’s innovators stay Ahead of What’s Possible.

The AI Labs team is looking for experienced Machine Learning Engineers to develop core AI technologies for Analog Devices’ future AI products. Our technologies range from generative AI for electronics to deeply embedded AI models in our silicon. We work across various markets and applications to solve problems beyond the reach of traditional algorithms and circuit innovations.

Responsibilities include:

• Full stack developer to perform AI experiments and R&D in AI / GenAI space.
• Test and deploy experimental frameworks and algorithms and evaluate performance, creating end-to-end experimental pipelines.
• Work with production coding counterparts to develop process to transition successful PoC code.
• Chip in with front end, devOps, distributed computing, etc. as needed
• Create and maintain reusable functional code in machine learning framework.
• Stay abreast of the latest developments in machine learning tools from reputable groups and experiment with and prototype new machine learning libraries and practices.

Qualifications:

• Master’s degree or equivalent experience.
• 5+ years of full-time industry experience in machine learning.
• Demonstrable track record of working with machine learning in production settings
• Strong background in machine learning, deep neural networks, reinforcement learning, and other AI technologies
• Hands-on experience with Large Language Models
• Proficiency in Python and software development practice
• Good understanding of neural network models (e.g., transformers, multimodal models, etc.)