Fleet Engineer

KLA•Phoenix, AZ

1d•$78,200 - $132,900•Onsite

About The Position

The successful fleet engineer will be responsible for measuring fleet performance, discovering opportunities for optimal availability and throughput, capturing and documenting insights and analysis. Responsibilities also include recommending analytical features, crafting data science models to tackle technology and process challenges at the local fab level. Strong communication and influencing skills will be essential in delivering against company's objectives.

Requirements

Strong analytical and problem-solving skills to identify and resolve complex tool-related issues.
Excellent attention to detail, ensuring accurate analysis and identification of excursions or outliers.
Proficient in programming languages (such as Python), statistical analysis techniques, data visualization tools, and semiconductor process control methodologies.
Proficiency in interpreting, developing, and modifying Shell and Python scripts to automate tasks and improve efficiency.
Experience working with dedicated analytical tools used in the semiconductor industry for real-time data analysis and monitoring, such as JMP and SQL.
Strong communication and influencing skills to collaborate with other teams, present findings, propose solutions, and engage with local teams and customers.
Ability to work in a fast-paced and dynamic environment, quickly adapting to changing priorities and requirements.
Up-to-date knowledge of semiconductor manufacturing processes, process control methodologies, and equipment technologies.
Be familiar with Linux and command line operations for efficient tool configuration, and data analysis tasks.
Demonstrated ability working in the semiconductor industry, with the focus on areas including but not limited to process control, lithography, fab equipment management

Responsibilities

Fleet Management: Ensure the fleet and individual semiconductor equipment tools meet commitments in terms of availability, throughput, and consistency.
Tool Connectivity: Ensure the data pipelines between the process control tools and the dedicated analytical platform work as expected.
Statistical Analysis: Conduct statistical analysis on tool data and component performance to identify trends, patterns, and tackle potential issues that impact fleet of tools.
Excursion Identification: Monitor tool behavior and data to identify excursions, anomalies, or deviations from expected performance and collaborate with the appropriate partners to facilitate root cause analysis.
Fleet: Regularly assess the availability and performance of the tool fleet, measuring throughput and discovering opportunities to optimize the availability and throughput combination.
Performance and Configuration Matching: Ensure consistency and alignment in tool performance and configurations across the fleet, maintaining high standards of quality and reliability.
Teamwork: Engage with internal and external partners to cultivate effective collaboration, understand their requirements, address concerns, and to build strong partnerships in dynamic matrix organization.
Impact the product: Assess local teams' and customers' feedback, and recommend features that would address the gaps and improve analytical platform, tool performance, and user experience.
Documentation: Capture actions and analysis against new insights, document reasoning and analysis, and assemble lessons learned.
Continuous Improvement: Stay updated with the latest advancements in process control tools, analyze industry trends, and propose innovative solutions to enhance tool performance, availability, and throughput. Streamline the feature requests by abiding to design for excellence principles.