Staff Research Scientist, Artificial Intelligence

About Analog Devices

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, AI, and software technologies into solutions that combat climate change, reliably connect humans and the world, and help drive advancements in automation and robotics, mobility, healthcare, energy and data centers. With revenue of more than $11 billion in FY25, ADI ensures today's innovators stay Ahead of What's Possible. Learn more at www.analog.com and on LinkedIn and X.

The Analog Garage is ADI’s Innovation Lab, located in the heart of downtown Boston. We pioneer breakthrough technologies to solve high-impact problems that drive tangible value. Bringing together engineers, research scientists, and business leaders, we develop new technologies and solutions in a fast-moving, experiment-focused startup atmosphere.

The Role

The Algorithmic Solutions Group develops cutting-edge, efficient algorithms to bring intelligence to the physical world. We fuse state-of-the-art machine learning with deep domain expertise to convert raw physical data into actionable insights, solving the hard problems where off-the-shelf solutions fall short.

We are seeking a Staff Research Scientist, Artificial Intelligence to operate at the intersection of modern AI and the physical world. This position challenges you to rethink AI breakthroughs, extending them beyond text and images to master complex physical signals—from multimodal sensory data to precision actuators and RF systems. You will architect and validate novel solutions that fuse modern AI with ADI technologies at the edge.

Key Responsibilities

Strategic Problem Definition: Collaborate with business leads and domain experts to identify opportunities where Modern AI can solve previously impossible problems. You will filter "hype" from "value," focusing on challenges that require deep technical innovation rather than off-the-shelf models.

• Research-to-Product: Lead technical execution from mathematical conceptualization to proof-of-concept. You will partner with researchers and engineers across the organization to bridge the gap between abstract research papers and validated solutions.
• Architecting Physical AI: Design next-generation neural architectures and custom training paradigms tailored to the physics of the data. You will investigate the inner workings of training dynamics and loss landscapes to develop robust learning strategies for complex physical signals.
• Efficient AI: Bridge the gap between massive foundation models and edge constraints. You will research techniques in model distillation, optimization, and neural architecture search to deploy "Modern AI" on efficient compute platforms.
• Thought Leadership: Maintain a deep awareness of the global AI research landscape. You will bring the best ideas from the academic community into ADI and mentor junior engineers.

The Ideal Candidate

You are a rigorous researcher and a pragmatic builder who thrives on complexity. You bring a "first-principles" understanding of deep learning, capable of deriving and modifying architectures from scratch.

• Educational & Professional Background: You hold a PhD degree in Computer Science, Electrical Engineering, or related area, and have 3+ years of industry experience translating complex theory into working systems.
• Deep Expertise in Modern AI: You possess deep technical mastery of modern architectures such as Transformers, State Space Models (e.g., Mamba), and Diffusion Models. You are equally comfortable with advanced training paradigms such as Self-Supervised Learning (SSL), Reinforcement Learning, and Flow Matching, or techniques for learning from limited data (few-shot/meta-learning). You understand the mathematics behind these methods and can adapt them to novel modalities.
• Engineering Excellence: You combine theoretical depth with expert-level proficiency in PyTorch or JAX. You are experienced in developing, deploying, and optimizing models using modern frameworks and cloud platforms.
• Innovation Mindset: You navigate the ambiguity of early-stage innovation with creative persistence, translating open challenges into con