Product Engineer 2 - AI/Data Science

Lam Research International Holding Company
Fremont, CA, United States
8 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Compensation
$86,000.0 - $183,000.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Data Analysis Systems Engineering Big Data Computer Programming Decision Support Systems Experimental Data Python (Programming Language) Machine Learning Regression Analysis Scientific Computating Statistical Process Control (SPC)
+3 more
Information Technology Data Analytics Tools for Reporting

Job description

In the Global Products Group, we are dedicated to excellence in the design and engineering of Lam’s etch and deposition products. We drive innovation to ensure our cutting-edge solutions are helping to solve the biggest challenges in the semiconductor industry. The impact you’ll make

Join Lam as a Product Engineer with expertise in Data Science and Advanced Analytics, where you’ll combine hands-on semiconductor experimentation with modern analytical methods to solve complex process and hardware challenges.

In this role, you will work directly with process development, technology development, product engineering, and customer escalations. You will design and execute experiments, develop advanced test vehicles, analyze data from multiple sources, and apply statistical and machine learning techniques to identify root causes, optimize processes, and uncover underlying physical mechanisms.

Operating at the intersection of semiconductor engineering, experimental science, and data analytics, you will transform laboratory and field data into actionable insights that improve product performance, accelerate technology development, and support data-driven engineering decisions. What you’ll do

This position is for a Product Engineer with Data Science specialization within the Selective Etch Product Group, part of the Global Products Group, based in Fremont, CA.

Process Development & Engineering

  • Perform process engineering research, development, characterization, and evaluation in support of Lam’s semiconductor capital equipment and systems.
  • Support new technology development, product qualification, and customer deployment activities.
  • 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 capability and reliability.
  • Compile and evaluate experimental data to establish process understanding and engineering recommendations.

Customer Escalations & Root Cause Analysis

  • Lead technical investigations associated with customer escalations by combining engineering fundamentals, experimental observations, and advanced analytics.
  • Apply statistical analysis, engineering judgment, and structured root-cause methodologies to identify failure mechanisms and drive corrective actions.
  • Partner with cross-functional teams to rapidly resolve product and process issues impacting customer performance.

Data Science, AI & Advanced Analytics

  • Develop predictive models and data-driven methodologies that improve understanding of process behavior and equipment performance.
  • Apply machine learning, artificial intelligence, statistical modeling, and advanced analytics techniques to laboratory, manufacturing, and field data sets.
  • Develop analytics tools, automated workflows, and visualization methods that enable engineers to efficiently analyze complex datasets.
  • Utilize data science methodologies to optimize experiments, improve process windows, accelerate root cause analysis, and support technology development.

Collaboration & Communication

  • Collaborate closely with process engineers, hardware engineers, systems engineers, field organizations, and customers to solve challenging technical problems.
  • Communicate technical findings and recommendations clearly to engineering teams, management, and customer stakeholders.
  • Contribute to building a culture of scientific rigor and data-driven decision making across the organization.

Requirements

  • PhD or Master’s degree in Materials Science, Mechanical Engineering, Electrical Engineering, Physics, Chemistry, Engineering Physics, or a related engineering or scientific discipline.
  • Demonstrated expertise in Data Science, Machine Learning, Artificial Intelligence, Applied Statistics, Scientific Computing, or Advanced Analytics.
  • Strong foundation in engineering fundamentals, experimental methods, and quantitative analysis.
  • Experience designing, executing, and interpreting laboratory, research, or engineering experiments.
  • Proven ability to apply statistical methods, machine learning, or AI techniques to scientific or engineering problems.
  • Programming experience with Python and commonly used scientific computing, machine learning, and data analytics libraries.
  • Strong communication skills with the ability to explain complex technical concepts to audiences with varied levels of expertise.
  • Passion for solving real-world engineering challenges through a combination of experimentation, data analysis, and scientific reasoning.

Candidates with advanced degrees in Data Science, Statistics, Computer Science, Applied Mathematics, or related quantitative disciplines may also be considered if they have demonstrated experience applying data science techniques to experimental, scientific, manufacturing, semiconductor, or engineering problems. Preferred qualifications

  • Semiconductor process, equipment, product engineering, or technology development experience.
  • Experience with semiconductor plasma, etch, deposition, surface science, or related applications.
  • Experience applying AI and machine learning techniques to physical systems, manufacturing processes, or scientific data.
  • Knowledge of Design of Experiments (DOE), Statistical Process Control (SPC), multivariate statistics, regression analysis, and predictive modeling.
  • Experience developing predictive models, anomaly detection algorithms, or engineering analytics tools.
  • Laboratory experience involving physics, chemistry, materials characterization, or semiconductor process development.
  • Experience translating experimental observations into predictive models and actionable engineering recommendations.
  • Familiarity with root cause analysis methodologies and failure analysis techniques.
  • Strong organizational skills and demonstrated ability to manage multiple technical projects simultaneously.
  • Excellent collaboration skills with the ability to work effectively in cross-functional and matrixed environments.

Benefits & conditions

CA San Francisco Bay Area Salary Range for this position: $86,000.00 -$183,000.00.

The above salary range for this position is relevant to applicants that reside or work onsite in the California, San Francisco Bay Area only. Salary offers will depend on factors that include the location you work from, your level, education, training, specific skills, years of experience and comparison to other employees already in this role. Actual salary may vary from salary offered due to numerous factors including but not limited to unpaid time off, unpaid leave, company mandated shutdown, and other relevant factors.

About the company

We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.

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