Crystal Growth Process Engineer

About the role

From smartphones to solar panels, innovative technology is needed to create the devices we use every day. Silfex’s silicon components help make that technology a reality. Silfex Inc., A Lam Research Company is the leading provider of precision silicon components used to make and operate semiconductor tools, which enable the trillion-dollar global electronics industry. Our company’s products are integral to the semiconductor equipment and optical markets. The outstanding team at Silfex makes that possible – through our people, we are advancing the world. The impact we have on the world is made possible by focusing on our people. So we recognize and celebrate our teams’ achievements. We strive to create an inclusive and diverse culture where everyone’s contribution and voice has value. We evaluate and evolve our offerings, so our people receive the support and empowerment to do meaningful things for their lives, careers, and communities. As a Crystal Growth Process Engineer you will develop innovative and scalable solutions for silicon crystal manufacturing, from applied research to mass production. As a process engineer, you will use applied research, data analysis and machine learning tools to continuously push the boundaries of process performance, equipment intelligence and manufacturing efficiency. In addition, this position provides technical oversight of crystal growing equipment and manufacturing processes, and cross-functional work with operations, maintenance and other stakeholders to achieve production goals. The process engineering role requires strong technical fundamentals, a learning mindset, a high level of initiative, effective communication skills and a methodical and organized approach to managing multiple project elements. Individuals who enjoy materials science, systems engineering, and manufacturing will find this role exciting and challenging as it allows you to think creatively and develop novel ideas from theory to mass production, reinventing processes for a new era of manufacturing where artificial intelligence, and human judgement work in a complimentary manner. This is a unique opportunity to combine operational responsibility with research and development, and this work is critical to the process performance, supply chains and competitiveness of our company and our customers.

Responsibilities

• Conduct process engineering research, development and evaluation in support of silicon crystal manufacturing.
• Utilize multi-physics simulations, materials testing and characterization techniques to establish the impact of manufacturing processes on critical material specifications and performance in customer applications.
• Conduct data analysis for process development and manufacturing, using and further developing novel approaches including machine learning and AI.
• Study scientific literature, research best practices from the semiconductor and other industries to develop novel ideas to improve manufacturing yield, quality and efficiency.
• Collaborate internally in a matrixed organization to support research and development and manufacturing.
• Effectively communicate technical information, manufacturing process performance and project plans.
• Provide technical leadership on the manufacturing floor, collaborating with manufacturing technicians.
• Adjust work schedule occasionally to support time-critical work.

Qualifications

• Bachelor’s degree with 5+ years of experience, or Master’s or PhD in materials science, chemical engineering, physics or related field.
• Experience doing hands-on experimental work in a laboratory, machine shop or industrial setting.
• Familiarity with microscopy and materials characterization methods such as optical and electron microscopy, x-ray diffraction and surface characterization techniques.
• Knowledge or experience with multi-physics simulations, including interpretation of data.
• Understanding of statistical process control and design of experiments.
• Strong data analysis skills, experience with statistical tools, basic knowledge of the applications of machine learning and AI models.
• Experience working in a collaborative or matrixed environment with diverse teams.