Lam Research Reliability Engineer 5Tualatin, ORFebruary 15, 2025

Reliability Engineer 5

Date:  Feb 15, 2025

Location:  

Tualatin, OR, US, 97062

Req ID:  181744

Worker Category:  On-site Flex

The Impact You’ll Make

Evaluates, from a reliability standpoint, the materials, properties and techniques used in production. Advises design engineering on selection, application and test of electronic components and systems. Recommends design or test methods and statistical process control procedures for achieving required levels of product reliability. Determines reliability requirements of components and systems to achieve company, customer and any governmental agency reliability objectives. Develops new acceleration techniques and analytical tools to assure the early identification of potential problems with new products, packaging, processes, and product reliability. Makes recommendations for changes in the selection and application of components and systems. May propose changes in design or formulation to improve system and/or process reliability.

What You’ll Do

• Predict, measure and analyze the reliability of mechanical designs, process specification and software programs for semiconductor manufacturing equipment. 
• Determine reliability of in service tools based upon quantitative field measured failure data and less quantitative quality metrics as measured by Lam Research. 
• Use advance statistical, probabilistic and forecasting methods to best quantify reliability of overall system. 
• Work directly with mechanical, electrical, process and software engineers to define reliability improvement plans, advanced testing methods such as HALT (Highly Accelerated Life Testing), and HASS (Highly Accelerated Stress Screening). 
• Develop methods that allow for correlation of these accelerated life testing methods to actual expected in service lives. 
• Data driven reliability through AI/ML methods, Utilizing DOE, Optimization, and statistical methods to create predictive reliability models.
• Stochastic optimization tools to bridge between simulation and experiments.
• Leading and conducting design reviews in cross functional and matrixed environments.
• Determines reliability requirements of components and systems to achieve company, customer and any industry standard reliability objectives.
• Perform analysis for reliability and tool availability, and help identify associated costs with deviation from targets
• Advises design engineering on selection, application and test of mechanical, electrical and electronic components and systems based on reliability data. 
• Performs FMEA, Block modeling and assists in other development activities like DoE, statistical analysis, and test planning.
• Recommends design or test methods and statistical process control procedures for achieving required levels of product reliability. Develop RQP (reliability qualification plans) and test plans (ALT, HALT, etc.) with optimal sample size.

Who We’re Looking For

• Strong ability and understanding of AI/ML concepts and hybrid physics-based AI/ML modeling software.
• Ability to work with a team to own and design concepts and drive design decisions.
• Make recommendations for changes in the selection and application of components and systems. May propose changes in design or formulation to improve system and/or process reliability.
• Develops new acceleration techniques and analytical tools to assure the early identification of potential problems with new products, packaging, processes, and product reliability. 
• Mine field, warranty and quality data to extract system and component failure information.
• Perform statistical analysis on field/test data and incorporate advanced analytical models for reliability and availability predictions.
• Write reports to summarize DFR activity and presents to product group engineers as necessary.
• Integrate the upcoming technology areas (e.g. AI, ML, IoT, Python, Data Analytics etc) to comprehend the impact on reliability analysis and improve the assessment methods

Preferred Qualifications

• Knowledge of AI/ML algorithm development, python, or related programming languages.
• Working knowledge of Reliability software, ReliaSoft, BlockSim, MADe, or other applicable software.
• PhD in Reliability Engineering, Mechanical Engineering or related field with reliability and statistical emphasis.
• Preferred knowledge of semiconductor metrology methods and employing sensors and hardware designs in a vacuum environments is a plus.