Senior Engineer - Test Solutions Engineering

Responsibilities

• Develop ATE (Automated Test Equipment) Test Solutions : Ceate detailed test plans, define experiments, and perform in-depth analyses to validate the yield, performance, and reliability of custom products.
• Ensure Quality and Performance : Develop test screening methods based on product application conditions, IP capabilities, design timing margins, and process technology specifications — all optimized for test time efficiency. Continuously refine these solutions through extensive ATE characterization and customer system feedback.
• Identify and Address Faults : Utilize a product’s DFT (Design for Test) solution to explore and bound the operating space, characterize silicon variations, and drive failure root-cause analysis. Establish robust test margins to protect product yields and improve quality.
• Cross-Functional Collaboration : Partner with design teams and customers to define DFT requirements and test strategy. Work closely with customers, design, DFT, operations, and reliability teams to ensure test solutions meet coverage, quality, and schedule requirements throughout the product lifecycle.

Requirements

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• 2+ years of experience in Product Engineering, Test Engineering, DFT, or Technology Characterization.
• Expertise in one or more of the following areas: Product Engineering and Test Development Automated Test Equipment (ATE), design-for-test methodology, statistics and data analysis techniques, semiconductor process technology and/or reliability and qualification methodologies
• Strong verbal and written communication skills, with the ability to clearly convey complex technical results to both engineering and cross-functional audiences.
• Proven analytical and problem-solving abilities, with a track record of driving root-cause analysis and engineering decisions under ambiguity.
• Proficiency in scripting and programming languages such as Python, Perl, or R within a Linux environment; experience applying AI and machine learning tools to accelerate data analysis, test optimization, or yield learning