Process Engineer 3

Lam Research•Fremont, CA

6d•$86,000 - $192,000

About The Position

Lam Research is seeking a highly motivated Process Engineer 3 to join its Global Metrology Team. The engineer will develop and implement advanced in-situ and analytical metrology solutions to accelerate process understanding, improve on-wafer performance, and support low-global-warming-potential process technologies with reduced carbon footprints. The role leads application of in-situ diagnostic techniques, including GP-FTIR, FTIR, mass spectrometry, UV-Vis, and Raman spectroscopy, to establish mechanistic understanding of process interactions and enable next-generation process control. It also uses analytical methods such as XPS, XRR, XRD, XRF, and FTIR to characterize process-induced surface modifications, investigate defect formation, and resolve technical challenges with cross-functional technology teams. The engineer develops data-driven metrology approaches using machine learning and deep learning to analyze process and spectral datasets, extract insights, and create predictive models linking process conditions, surface chemistry, and defectivity. The work includes predictive metrology frameworks and calibrated defectivity models for process optimization, simulation, and defect monitoring. The position collaborates with process, product, defect inspection, and simulation teams; evaluates and deploys emerging inspection and review technologies, including next-generation e-beam platforms; and recommends and implements metrology solutions supporting product competitiveness and future technology development. The engineer also establishes and executes SPC-based monitoring and qualification methods to maintain metrology asset performance, capability, and reliability.

Requirements

Bachelor's degree with at least 5 years of experience; or a master's degree in Materials Science, Chemical Engineering, Chemistry, Physics, or a related field with at least 3 years of experience; or a PhD with no previous professional experience; or equivalent experience.

Nice To Haves

Strong teamwork and collaboration skills and a customer-centric technology development approach.
Experience with AI techniques, including deep learning and CNNs, and Python programming.
Working knowledge of statistical analysis and problem-solving methodologies.
Familiarity with laboratory work and semiconductor equipment, including surface preparation and analytical techniques.
In-depth understanding of Statistical Process Control (SPC) and/or Design of Experiments (DOE).
Knowledge of material synthesis and material characterization.

Responsibilities

Develop and implement advanced in-situ and analytical metrology solutions.
Apply in-situ diagnostic techniques, including GP-FTIR, FTIR, mass spectrometry, UV-Vis, and Raman spectroscopy, to understand process interactions and support process control strategies.
Use analytical methods including XPS, XRR, XRD, XRF, and FTIR to characterize surface modifications, investigate defect formation, and address technical challenges.
Develop data-driven metrology approaches using machine learning and deep learning to analyze process and spectral datasets.
Create predictive models linking process conditions, surface chemistry, and defectivity.
Develop predictive metrology frameworks and calibrated defectivity models for process optimization, simulation, and defect monitoring.
Collaborate with process, product, defect inspection, and simulation teams on metrology and defectivity initiatives.
Evaluate and deploy emerging inspection and review technologies, including next-generation e-beam platforms.
Recommend and implement metrology solutions to support technical leadership, product competitiveness, and future technology development.
Establish and execute SPC-based monitoring and qualification methodologies for metrology assets.