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Experience
Experienced
About the role
This role sits in the Product Engineering team and focuses on creating and rolling out AI and machine learning solutions that reshape semiconductor manufacturing and engineering workflows. You will work with large-scale semiconductor datasets and advanced ML methods to tackle complex engineering problems, while also guiding Citizen Data Scientists through training and technical advice. It suits an experienced ML or AI practitioner who enjoys both hands-on model building and mentoring others in a cross-functional, fast-moving setting.
What you'll do
Build, test, and launch machine learning models for yield prediction, test time optimisation, reliability analysis, and manufacturing process improvement.
Use advanced analytics and ML methods on large structured and semiconductor manufacturing datasets.
Create scalable ML workflows and predictive solutions that produce actionable engineering insights.
Assess model performance and keep improving accuracy and effectiveness.
Design and build intelligent AI agents that automate engineering and operational workflows.
Develop AI-driven solutions for yield analysis, test program validation, root cause investigation, engineering report generation, and process optimisation.
Connect AI agents with enterprise platforms, collaboration tools, and business systems.
Work with engineering teams to acquire, clean, transform, and structure high-volume manufacturing, test, probe, and inline process data.
Build data pipelines and frameworks that support AI and machine learning applications.
Partner with deployment and architecture teams to ensure robust production implementation and scalable inferencing solutions.
Mentor and coach Citizen Data Scientists in machine learning methodologies and analytics best practices.
Create training materials, learning paths, workshops, and hands-on technical sessions.
Review AI/ML projects and give technical guidance to improve solution quality and business impact.
Promote a culture of data-driven decision-making and AI adoption across Product Engineering.
Collaborate with cross-functional engineering, manufacturing, data science, and IT teams to spot 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.
Keep up with emerging AI, machine learning, MLOps, and semiconductor industry technologies.
Support strategic AI initiatives and take part in technology roadmap discussions.
Integrate AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organisational standards and legal requirements.
Help build a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within your scope of work.
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Requirements
PhD with at least 2 years, or Master's degree with at least 5 years, or Bachelor's degree with at least 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
Strong programming skills in Python
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