Principal Engineer, Machine Learning

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). Prrincipal Machine Learning Engineer, Global Operations and Technology Analog Devices Overview Analog Devices operates a globally distributed manufacturing network that runs continuously to deliver high quality, high reliability products to customers worldwide. Our factories must operate 24x7, often with long process flows, tight tolerances, and complex interdependencies across tools, sites, and supply chain partners. Data and machine learning are increasingly central to how we monitor, optimize, and scale these operations. The Global Operations and Technology organization is building a modern analytics and machine learning foundation to support manufacturing and supply chain use cases across ADI. These capabilities power everything from demand-driven production planning to factory-level optimization, quality monitoring, and decision support. The Lead Machine Learning Engineer role focuses on turning models into reliable, production-grade systems that operate at global scale and meet the uptime, performance, and governance requirements of manufacturing environments. Role Description We are seeking a Lead Machine Learning Engineer to design, build, and operate the systems that deploy and run machine learning models across ADI manufacturing. This role is less about day-to-day model development and more about creating the platforms, integrations, and operational workflows that allow models to be used safely and effectively in production. You will work closely with data scientists, manufacturing engineers, IT partners, and platform teams to ensure models are integrated into factory systems, supply chain workflows, and analytics products. This role requires strong software and systems engineering skills, a solid understanding of machine learning concepts, and an appreciation for the operational realities of always-on manufacturing environments. Key Responsibilities

• Design and implement production-grade machine learning pipelines that support training, validation, deployment, and monitoring of models
• Build and maintain scalable systems for serving machine learning models in batch and near real-time manufacturing use cases
• Integrate machine learning solutions with factory systems, supply chain platforms, and enterprise data infrastructure
• Establish reliability, performance, and monitoring standards suitable for 24x7 global manufacturing operations
• Partner with data scientists to translate research and prototypes into robust, maintainable production solutions
• Implement MLOps practices including model versioning, automated testing, deployment automation, and rollback strategies
• Ensure solutions meet security, data governance, and compliance requirements
• Support a growing portfolio of manufacturing and supply chain use cases, including but not limited to forecasting, quality analytics, and operational optimization
• Provide technical leadership and mentorship on machine learning systems design and best practices

Required Qualifications And Experience

• Strong experience building and operating production software systems that support machine learning or data-intensive applications
• Hands-on experience deploying and serving machine learning models at scale using common ML frameworks and libraries
• Solid understanding of machine learning concepts, model lifecycles, and tradeoffs, even if not focused on model research
• Proficiency in Python and experience with backend or platform development
• Experience working with distributed systems, cloud or hybrid environments, and modern data infrastructure
• Ability to design for reliability, observability, and maintainability in always-on operational environments
• Experience collaborating across data science, engineering, manufacturing, and IT teams

Preferred Qualifications

• Master’s or PhD in computer science, engineering, applied mathematics, or a related quantitative field
• Experience supporting manufacturing, industrial, or supply chain systems
• Familiarity with MLOps tooling and practices for model deployment, monitoring, and lifecycle management
• Experience with streaming or event-driven architectures used in operational systems
• Track record of leading complex technical initiatives and influencing system design across teams

Why Analog Devices This role offers the opportunity to build the backbone that enables machine learning to operate reliably in one of the most demanding environments in the industry. You will help shape how advanced analytics are integrated into global manufacturing operations, working on systems that must perform continuously and at scale. At Analog Devices, you will tackle technically challenging problems with real-world impact, supporting the technologies that power modern life. 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