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Lumilens is building photonics infrastructure for AI supercomputing, developing chip-to-chip optical interconnects and scalable photonic engines. The company is Series B funded and led by veterans from transformative technology companies.
As Staff Equipment Engineer for Advanced Packaging, you will own the complete lifecycle of semiconductor manufacturing equipment, from procurement and facility setup through optimization and maintenance. This is a critical technical role requiring deep expertise in wafer-level assembly machinery and a focus on minimizing downtime through predictive maintenance.
Key responsibilities include:
- Equipment Lifecycle Management: Lead evaluation, selection, procurement, setup, and qualification of new manufacturing equipment and facility infrastructure.
- Advanced Tool Ownership: Serve as subject matter expert for advanced packaging and wafer-level assembly equipment including back-grinders, stealth dicers, expanders, flip-chip bonders, pick-and-place systems, reflow ovens, and solder paste printers.
- Uptime Optimization: Own equipment uptime across the production floor, proactively minimizing unscheduled downtime.
- Maintenance Strategy: Design and execute periodic and predictive maintenance programs ensuring operational efficiency and yield.
Required qualifications:
- Bachelor's degree in Mechanical Engineering, Electrical Engineering, Mechatronics, or related discipline.
- Extensive hands-on experience operating, troubleshooting, and maintaining advanced packaging and wafer-level assembly equipment.
- Proven track record defining equipment specifications, driving vendor selection, and completing successful machine buy-offs (FAT/SAT).
- Strong analytical skills for root-cause analysis and implementing permanent corrective actions.
- Experience establishing predictive maintenance protocols in high-tech manufacturing or cleanroom environments.
This role offers competitive salary, career advancement opportunities, and the chance to work with a world-class team on cutting-edge photonics and AI infrastructure challenges.
