Senior Engineer Product Test Engineering

Your Role

Key responsibilities in your new role

• Support Maverick lots (lots-on-hold) detection / handling, analysis, disposition & improvement against reoccurrence, address issues to Front end /assembly.
• Execute and implement Ratio activities (test time reduction, retest reduction, test insertion removal, higher parallelism Migration).
• Interfaces with design, process, test, reliability and manufacturing engineering to solve product issues and production problems in terms of yield, stability and quality.
• Develops and sustains process improvements to reduce production costs and increase yields.
• Provide customer return verification support including implement containment & preventive actions.
• Perform complex analysis of large data sets to derive statistically dependent outputs, leading to observations and recommendations for testing process improvements.
• Interpret manufacturing and testing data to gain insights into testing performance, identifying areas for future improvement and growth.
• Develop and implement semi-automated data analysis algorithms using programming languages and data analysis tools, and design reporting systems to support technology maturation and production efforts.
• Advise product engineer teams on AIML techniques to further tune current testing processes, driving efficiency and effectiveness.
• Collaborate with cross-functional teams to convey data analysis results, observations, and recommendations in both written and interpersonal communication formats.
• Support products as a learning curve for data analytics and improvement processes, driving a culture of continuous learning and improvement.

Your Profile

Qualifications and skills to help you succeed

• Bachelor's or Master's degree in Electrical Engineering (EE), Mechanical Engineering (ME), or a related field.
• Min. 0-5 years of experience in product testing, manufacturing, or a related field, with a strong desire to transition into an AIML-focused role.
• Strong foundation in programming languages, such as Python, C++, or MATLAB, and experience with data analysis tools and software.
• Basic understanding of AIML concepts, including machine learning, deep learning, and natural language processing.
• Excellent communication and interpersonal skills, with the ability to work effectively in a collaborative team environment.
• Strong analytical and problem-solving skills, with the ability to derive insights from complex data sets.