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.

          

Software & Digital Platforms

Principal AI/ML Engineer - Edge AI and Physical Intelligence

Job Description: 

Bridge intelligence from silicon to the physical world. We are looking for a Principal AI/ML Engineer to lead the development of Edge AI and Physical Intelligence capabilities for embedded and semiconductor platforms, enabling intelligent sensing, real-time inference, and autonomous decision-making close to the source of data. This role will define technical strategy, architect production-grade AI/ML solutions, and optimize models for ADI-relevant edge platforms spanning microcontrollers, DSPs, sensor systems, mixed-signal devices, industrial automation, robotics, automotive, digital healthcare, and intelligent instrumentation. The successful candidate will work closely with software, firmware, hardware, systems, applications, and product teams to translate advanced AI/ML concepts into efficient, reliable, and scalable solutions that help customers sense, interpret, and act in the physical world.

Key Responsibilities:

• Lead the architecture, design, and delivery of Edge AI and Physical Intelligence solutions for embedded, semiconductor, intelligent sensing, industrial, robotics, automotive, and digital healthcare platforms.
• Develop, optimize, and deploy AI/ML models for low-latency, power-efficient inference on microcontrollers, DSPs, NPUs, GPUs, FPGAs, and heterogeneous edge compute platforms.
• Drive model compression, quantization, pruning, distillation, hardware-aware optimization, and runtime integration to meet accuracy, latency, memory, thermal, and power targets on resource-constrained devices.
• Design AI solutions for multimodal sensing, sensor fusion, computer vision, audio, vibration, radar, time-series analytics, anomaly detection, predictive maintenance, condition-based monitoring, and closed-loop control.
• Collaborate with embedded software, firmware, hardware, systems, applications, field engineering, and product teams to define requirements and deliver customer-ready intelligent edge reference solutions.
• Provide technical leadership and mentorship to engineers, setting standards for AI/ML engineering excellence, responsible AI, reproducibility, testing, and production readiness.
• Evaluate emerging AI/ML frameworks, embedded runtimes, accelerators, and toolchains to guide technology selection and platform strategy for ADI-relevant markets.
• Translate customer, product, and system-level needs into measurable AI performance requirements, trade-offs, benchmarks, and technical roadmaps.
• Produce clear technical documentation, including architecture specifications, model evaluation reports, benchmark results, deployment guides, and best-practice playbooks.

Requirements:

• Bachelor’s degree in Computer Engineering, Electrical/Electronics Engineering, Computer Science, Robotics, Data Science, Applied Mathematics, or a related field; Master's or PhD degree is preferred.

• At least 10 years of related engineering experience, including significant hands-on experience in production AI/ML, embedded AI, computer vision, signal processing, robotics, or intelligent edge systems.
• Deep expertise in machine learning fundamentals, deep learning architectures, model evaluation, data pipelines, and deployment to constrained or heterogeneous compute environments.
• Strong programming skills in Python and C/C++, with experience building reliable software for embedded Linux, RTOS, bare-metal, or heterogeneous compute platforms.
• Experience with AI/ML frameworks and deployment toolchains such as PyTorch, TensorFlow, ONNX, TensorFlow Lite, or similar technologies.
• Experience deploying AI models on edge AI accelerators, embedded GPUs, NPUs, DSPs, FPGAs, microcontrollers, or custom silicon.
• Demonstrated experience optimizing models for edge constraints, including latency, memory footprint, compute efficiency, thermal limits, deterministic behavior, and power consumption.
• Strong understanding of embedded systems, sensor interfaces, digital signal processing, real-time constraints, hardware-software co-design, and system-level trade-offs in semiconductor-based platforms.
• Experience with computer vision, audio/speech processing, sensor signal processing, sensor fusion, robotics perception, control systems, or physical-world AI applications.
• Ability to debug complex AI-enabled systems across models, data, software, firmware, hardware, sensor behavior, and system integration issues.
• Proven technical leadership in setting architecture direction, influencing cross-functional teams, mentoring engineers, and driving execution across ambiguous problem spaces.
• Strong communication skills, with the ability to explain AI/ML, embedded, and semiconductor trade-offs, risks, and recommendations to both technical and non-technical stakeholders.
• Knowledge of Agile/Scrum methodologies and experience working in distributed, cross-functional engineering teams.

Nice to Have:

• Experience with robotics frameworks such as ROS/ROS2, motion planning, SLAM, reinforcement learning, or autonomous systems.
• Knowledge of TinyML, structured pruning, federated learning, continual learning, on-device adaptation, or privacy-preserving AI techniques.
• Experience with hardware-in-the-loop testing, simulation environments, digital twins, synthetic data generation, evaluation boards, or real-world model validation.
• Familiarity with industrial automation, motor control, condition-based monitoring, robotics, automotive sensing, digital healthcare, instrumentation, or other ADI-relevant application domains.
• Familiarity with functional safety, cybersecurity, responsible AI, and regulatory considerations for AI-enabled physical systems.
• Experience contributing to open-source AI/ML, embedded systems, robotics, edge computing, or developer toolchain projects.
• Experience using GenAI tools to accelerate software development, model evaluation, documentation, or engineering workflows.

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.

Job Req Type: Experienced

          

Required Travel: Yes, 10% of the time

          

Shift Type: 1st Shift/Days