Principal AI/ML Engineer

Job Title

Principal AI/ML Engineer

Role Summary

Lead the architecture and delivery of Edge AI and Physical Intelligence solutions for embedded and semiconductor platforms. The role focuses on production-grade model development, hardware-aware optimization, and cross-functional integration to enable low-latency, power-efficient inference on resource-constrained devices.

Work closely with software, firmware, hardware, systems, applications, and product teams to translate AI/ML research into reliable, scalable edge deployments across industrial, robotics, automotive, and healthcare domains.

Experience Level

Senior-level. The role requires significant experience; the posting requests at least 10 years of related engineering experience.

Responsibilities

Own technical strategy and delivery for AI/ML solutions on edge platforms; provide hands-on leadership and cross-team coordination.

• Architect, design, and deliver Edge AI and Physical Intelligence solutions for embedded systems and intelligent sensing platforms.
• Develop, optimize, and deploy models for low-latency, power-efficient inference on microcontrollers, DSPs, NPUs, GPUs, FPGAs, and heterogeneous compute.
• Perform model compression, quantization, pruning, distillation, and hardware-aware optimization to meet accuracy, latency, memory, thermal, and power targets.
• Design multimodal sensing solutions: sensor fusion, computer vision, audio, vibration, radar, time-series analytics, anomaly detection, and closed-loop control.
• Integrate models with embedded runtimes and production software stacks; ensure reproducibility, testing, and production readiness.
• Provide technical leadership and mentorship; set engineering standards and best practices for responsible AI and deployment.
• Evaluate AI/ML frameworks, accelerators, and toolchains to guide platform strategy and technology selection.
• Translate customer and system-level needs into measurable performance requirements, benchmarks, and roadmaps.
• Produce clear architecture specifications, benchmark reports, deployment guides, and documentation for cross-functional teams.

Requirements

Must-have technical skills, domain experience, and leadership abilities required for the role.

• At least 10 years of engineering experience in production AI/ML, embedded AI, computer vision, signal processing, robotics, or intelligent edge systems.
• Deep knowledge of machine learning fundamentals, deep learning architectures, model evaluation, and data pipelines.
• Strong programming skills in Python and C/C++; experience building reliable software for embedded Linux, RTOS, bare-metal, or heterogeneous platforms.
• Experience with AI/ML frameworks and deployment toolchains such as PyTorch, TensorFlow, ONNX, TensorFlow Lite, or similar.
• Experience deploying models on edge accelerators, embedded GPUs, NPUs, DSPs, FPGAs, microcontrollers, or custom silicon.
• Proven ability to optimize models for latency, memory footprint, compute efficiency, thermal limits, determinism, and power consumption.
• Strong understanding of embedded systems, sensor interfaces, DSP, real-time constraints, and hardware-software co-design.
• Experience debugging complex AI-enabled systems across models, data, software, firmware, hardware, sensor behavior, and system integration.
• Proven technical leadership: setting architecture direction, influencing cross-functional teams, mentoring, and driving execution in ambiguous problem spaces.
• Effective communication skills for technical and non-technical stakeholders; experience in Agile/Scrum and distributed engineering teams.

Nice-to-have:

• Experience with ROS/ROS2, SLAM, motion planning, reinforcement learning, or autonomous systems.
• Knowledge of TinyML, federated learning, continual learning, on-device adaptation, or privacy-preserving AI.
• Experience with hardware-in-the-loop testing, simulation, synthetic data, evaluation boards, or real-world validation.
• Familiarity with industrial automation, motor control, automotive sensing, digital healthcare, functional safety, cybersecurity, or regulatory considerations.
• Contributions to open-source projects or experience using GenAI tools to accelerate engineering workflows.

Education Requirements

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

About the Company

Company: Analog Devices

Headquarters: Norwood, Massachusetts, USA

Analog Devices is a leading global semiconductor company that bridges the physical and digital worlds, enabling breakthroughs at the Intelligent Edge. With a focus on innovation, ADI develops solutions that drive advancements in digitized factories, mobility, and digital healthcare. The company employs around 24,000 people globally and reported revenues exceeding $9 billion in FY24, creating technologies that transform lives across various sectors.