Process Engineer - AI/Data Science

Join Lam as a process engineer – AI/Data Science embedded in an experimental-focused process team, where you'll design, develop, and program methods to analyze unstructured and data into actionable insights. You’ll engage in lab experimentation on Lam’s products and develop advanced test vehicles to generate data input for analysis. You'll develop algorithms and automated processes to evaluate complex data sets from disparate sources. Your expertise in generating, interpreting, and communicating actionable insights enables Lam to make informed and data-driven decisions.

Responsibilities

Design, develop, and program methods to analyze unstructured and data into actionable insights; Engage in lab experimentation on Lam’s products and develop advanced test vehicles to generate data input for analysis; Develop algorithms and automated processes to evaluate complex data sets from disparate sources; Perform professional process engineering research, development, and evaluation in support of the company’s complex semiconductor capital equipment and systems; Focus from concept and feasibility through onsite equipment evaluation with a balanced approach between advanced data science and 'hands-on' experimentation; Develop predictive models derived from early experimentation to infer physical mechanisms within a collaborative multi-disciplinary team; Develop advanced test vehicles and apply systematic root cause analysis; Compile and evaluate test data to determine appropriate limits and variables for process specifications

Requirements

Ph.D. or Master’s degree in chemical engineering, materials science, chemistry or engineering physics with a strong background in advanced data science and machine learning with a minimum of 0-2 years work experience; Demonstrated expertise and experience in data science, machine learning, artificial intelligence or advanced analytics; Experimental laboratory experience to refine data collection and analysis; Candidates with advanced degrees in Data Science, Statistics, Computer Science, Engineering, or Applied Mathematics will be considered if they have demonstrated experience applying data science techniques to experimental, engineering or semiconductor problems; Strong communication skills, with the ability to explain technical results clearly to audiences with varied levels of technical expertise

Nice to have

Expertise applying AI and machine learning methodologies to physical systems; Experience unifying experimental results into predictive models for actionable insights; Experimental laboratory experience in semiconductors; Chemistry laboratory experience; Knowledgeable with statistical analysis and modeling including Statistical Process Control (SPC), Design of Experiments (DOE) and other data science methodologies; Surface science knowledge a plus; Strong organizational skills and demonstrated ability to manage multiple tasks simultaneously and ability to react to shifting priorities to meet business needs and deadlines; Excellent people skills with demonstrated ability to work effectively and efficiently with diverse teams, customers, internal and external partners; Collaboration/ Matrix environment mindset