Product Engineer II: Data Science for Semiconductors

Lam Research; Fremont (CA); Hybrid; USD 86,000 - 183,000; Full time

Benefits offered by this job

On-site Flex

Virtual Flex

Hybrid work model

Employee benefits

Job summary

Lam Research in Fremont, CA, is seeking a Product Engineer with a Data Science specialization to blend semiconductor experimentation with modern analytics. You will design experiments, analyze multi-source data, and apply statistical and ML techniques to identify root causes, optimize processes, and drive engineering decisions.

Collaborating with process development, hardware and field teams, you will transform lab and field data into actionable insights that improve product performance and

Qualifications

• PhD or Master’s degree in Materials Science, Mechanical Engineering, Electrical Engineering, Physics, Chemistry, Engineering Physics, or related field.
• Demonstrated expertise in Data Science, Machine Learning, AI, Applied Statistics, Scientific Computing, or Advanced Analytics.
• Strong foundation in engineering fundamentals, experimental methods, and quantitative analysis.
• Experience designing, executing, and interpreting laboratory or engineering experiments.
• Proficiency in Python and scientific computing libraries.

Responsibilities

• Perform process engineering R&D, characterization and evaluation for Lam’s semiconductor equipment.
• Design and analyze experiments to investigate process, hardware, and system-level performance.
• Develop advanced test vehicles and apply problem-solving to improve product capability and reliability.
• Lead technical investigations for customer escalations using analytics and DOE-based methods.
• Develop predictive models and analytics tools to assess equipment performance.

Skills

Data Science

Machine Learning

Statistics

Python

Education

PhD in STEM

Master's in STEM

Job description

Lam Research in Fremont, CA, is seeking a Product Engineer with a Data Science specialization to blend semiconductor experimentation with modern analytics. You will design experiments, analyze multi-source data, and apply statistical and ML techniques to identify root causes, optimize processes, and drive engineering decisions.

Collaborating with process development, hardware and field teams, you will transform lab and field data into actionable insights that improve product performance and