Principal/Staff ML/AI Engineer, Product Engineering, STPG

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Job Summary: Join the Product Engineering team to develop and deploy Artificial Intelligence (AI) and Machine Learning (ML) solutions that transform semiconductor manufacturing and engineering workflows. This role is responsible for building predictive analytics models, developing agentic AI solutions, enabling intelligent automation, and driving data-driven decision-making to improve yield, quality, cycle time, reliability, and cost efficiency. The successful candidate will leverage advanced machine learning techniques, large-scale semiconductor datasets, and AI technologies to solve complex engineering challenges. In addition, this role will mentor and enable Citizen Data Scientists (CDS) by providing technical guidance, training, and best practices in machine learning, analytics, and AI adoption. Strong technical expertise, innovation, collaboration, and communication skills are essential for success. Main Responsibilities: Machine Learning Development • Develop, validate, and deploy machine learning models for yield prediction, test time optimization, reliability analysis, and manufacturing process improvement. • Apply advanced analytics and machine learning techniques to large-scale structured and semiconductor manufacturing datasets. • Build scalable ML workflows and predictive solutions that generate actionable engineering insights. • Evaluate model performance and continuously improve model accuracy and effectiveness. Agentic AI Development • Design and develop intelligent AI agents to automate engineering and operational workflows. • Build AI-driven solutions for applications such as yield analysis, test program validation, root cause investigation, engineering report generation, and process optimization. • Integrate AI agents with enterprise platforms, collaboration tools, and business systems. Data Engineering & Analytics • Partner with engineering teams to acquire, cleanse, transform, and structure high-volume manufacturing, test, probe, and inline process data. • Develop data pipelines and frameworks that support AI and machine learning applications. • Collaborate with deployment and architecture teams to ensure robust production implementation and scalable inferencing solutions. Citizen Data Scientist (CDS) Enablement • Mentor and coach Citizen Data Scientists in applying machine learning methodologies and analytics best practices. • Develop training materials, learning paths, workshops, and hands-on technical sessions. • Review AI/ML projects and provide technical guidance to improve solution quality and business impact. • Foster a culture of data-driven decision-making and AI adoption across Product Engineering. Other Responsibilities: • Collaborate with cross-functional engineering, manufacturing, data science, and IT teams to identify opportunities for AI-driven improvements. • Drive innovation initiatives that reduce test time, improve yield, enhance product quality, and automate manual processes. • Contribute to technical publications, patent disclosures, engineering standards, and internal best practices. • Stay current with emerging AI, machine learning, MLOps, and semiconductor industry technologies. • Support strategic AI initiatives and participate in technology roadmap discussions. AI Responsibilities: • Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements • Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work. Minimum Required Qualifications/Experience • PhD with ≥2 years, or Master’s degree with ≥5 years, or Bachelor’s degree with ≥7 years of relevant experience in Computer Science, Data Science, Electrical/Electronic Engineering, Artificial Intelligence, or a related field • Minimum of 6 years of relevant industry experience in machine learning, data science, or AI solution development. • Proven experience developing and implementing machine learning solutions in production environments. • Experience working with large-scale structured datasets and predictive analytics applications. • Demonstrated ability to lead technical initiatives and collaborate effectively across multidisciplinary teams. Must Have Technical Skills • Strong programming skills in Python. • Proficiency with data analytics and machine learning libraries such as Pandas, NumPy, Scikit-learn, and related tools. • Strong understanding of supervised and unsupervised machine learning techniques. • Experience with regression models, decision trees, random forests, gradient boosting, and predictive modeling. • Ability to develop, validate, and optimize machine learning models for business and engineering applications. • Experience handling large-scale datasets and building end-to-end ML workflows. • Understanding of statistical analysis, feature engineering, model evaluation, and data visualization. • Familiarity with software development best practices and version control systems. Must Have Soft Skills • Strong analytical and problem-solving skills. • Excellent communication and presentation abilities. • Ability to explain complex technical concepts to both technical and non-technical audiences. • Strong collaboration and stakeholder management skills. • Self-motivated with a continuous learning mindset. • Ability to wor…