This role pays less than
85%
of similar roles. Most pay
$145,925–$219,650
— the shaded band above.
At the midpoint, this role pays about
$134k
versus about
$183k
for comparable roles.
Based on 240 similar postings.
Employer
About Lam Research
Lam Research Corporation is a leading American supplier of wafer-fabrication equipment and services to the global semiconductor industry.
Lam Research currently has
299 open roles
on FindRole.
Listed pay typically runs
$114,000–$253,000
across 141 roles with salary data.
Product Engineer 2 - AI/Data Science joins the Global Products Group within the Selective Etch Product Group to address complex process and hardware challenges in the semiconductor industry. This role involves designing and executing experiments, developing advanced test vehicles, and performing root cause analysis for customer escalations. The engineer will transform laboratory and field data into actionable insights by applying statistical modeling, machine learning, artificial intelligence, and advanced analytics to optimize process windows and improve product performance. Key responsibilities include building predictive models, automated workflows, and visualization tools to support data-driven engineering decisions. Candidates must possess expertise in Python and scientific computing libraries alongside a strong foundation in experimental methods. The role focuses on solving technical problems related to semiconductor plasma, etch, deposition, and surface science through a combination of rigorous experimentation and advanced data science methodologies.
Design, execute, and analyze experiments to investigate process, hardware, and system-level performance.
Develop advanced test vehicles and apply systematic problem-solving methodologies to improve product reliability.
Lead technical investigations for customer escalations using engineering fundamentals and advanced analytics.
Apply machine learning, artificial intelligence, and statistical modeling to laboratory and manufacturing datasets.
Create automated workflows, predictive models, and visualization tools to analyze complex data.
Translate experimental observations into actionable engineering recommendations to optimize process windows.
Perform research and characterization to support new technology development and product qualification.
What we're looking for
PhD or Master's degree in Materials Science, Mechanical Engineering, Electrical Engineering, Physics, Chemistry, Engineering Physics, or a related field.
Candidates with advanced degrees in Data Science, Statistics, Computer Science, or Applied Mathematics may be considered with relevant experience.
Demonstrated expertise in Data Science, Machine Learning, Artificial Intelligence, Applied Statistics, Scientific Computing, or Advanced Analytics.
Experience designing, executing, and interpreting laboratory, research, or engineering experiments.
Programming experience with Python and common scientific computing, machine learning, and data analytics libraries.
Strong foundation in engineering fundamentals, experimental methods, and quantitative analysis.
Ability to communicate complex technical concepts clearly to diverse audiences.
Semiconductor process, equipment, product engineering, or technology development experience (preferred).
Artificial Intelligence
Machine Learning
Data Science
Statistical Process Control (SPC)
Design of Experiments (DOE)
Root Cause Analysis
Surface Science
Chemistry
Advanced Analytics
Statistics
Datacenter Systems
CPU
GPU
AI
Machine Learning
High-Performance Computing
Linux
Unix
Python
Bash
PCIe
Firmware
System Architecture
Manufacturing Engineering
Validation
Thermal Management
Power Delivery
Networking