Staff Edge AI/ML Scientist

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, 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 $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible™. Learn more at www.analog.com and on LinkedIn and Twitter (X).

Staff Edge AI/ML Scientist

Location: Boston, MA, SJ

Team: MicroAI

Role Summary:

We are building a pioneering organization focused on advancing the next generation of Edge AI compute and intelligent sensors. We are seeking a Staff Edge AI/ML Scientist to research, develop, and test lightweight learning models on state-of-the-art edge compute platforms. In this role, you will initiate academic collaborations, prototype and evaluate AI models for on-device adaptation, and assess new techniques for optimization, distillation, and compilation. Your work will directly contribute to real-world applications in wearables, audio, robotics, and other streaming sensor use cases.
Key Responsibilities

• Lead meaningful collaborations with academia on novel compression and optimization approaches.

• Optimize and re-architect AI models to ensure maximum efficiency across edge compute modalities.

• Benchmark and develop lightweight learning models suitable for constrained edge devices operating at ultra-low power with limited memory.

• Collaborate with cross-functional team members toward an integrated HW + SW compute solution.

• Evaluate trade-offs in model accuracy, memory footprint, compute cost, and latency across different edge platforms.

• Collaborate with the compute architecture team to align model structures with hardware architecture.

Ideal Profile

• Master’s or PhD in Artificial Intelligence, Electrical Engineering, Computer Science, or a related field, with a strong focus on machine learning or embedded AI.

• 7+ years of advanced experience in HW centric model compression and optimization, and deep knowledge in machine learning models, including CNNs, RNNs, Transformers, continual learning, and on-device retraining.

• Proven experience conducting co-research with academia, driving meaningful breakthroughs in hardware-centric model compression and optimization.

• Hands-on experience with major ML frameworks such as PyTorch or TensorFlow, and deployment tools like TensorFlow Lite, TVM, or ONNX.

• Strong analytical mindset with the ability to balance performance, power, and memory tradeoffs.

• Excellent collaboration and documentation skills, with a proactive attitude in a fast-paced, crossdisciplinary environment.

• Big Advantage:

Experience with SNN frameworks or converting ANN to SNN, advanced optimization, and compilation techniques.

Experience in neuromorphic computing, analog computing, or embedded

systems development

For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export  licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls.  As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.

Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.

EEO is the Law: Notice of Applicant Rights Under the Law.

• Actual wage offered may vary depending on work location, experience, education, training, external market data, internal pay equity, or other bona fide factors.

• This position qualifies for a discretionary performance-based bonus which is based on personal and company factors.

• This position includes medical, vision and dental coverage, 401k, paid vacation, holidays, and sick time, and other benefits.