Manufacturing Engineer, Battery Dispense Process

What to Expect

Tesla is looking to hire a Sr. Manufacturing Engineer to own factory deployment and production ramp of high-voltage battery dispense processes for Optimus. You'll work at the intersection of product, process, and automation, industrializing cutting-edge from Battery Joining processes, driving equipment design and validation, and delivering yield, quality, and cycle time performance through launch and volume ramp.

What You’ll Do

• Collaborate closely with the process development team to deploy and scale highly automated dispense processes from prototype to stable and fully validated

• Guide cross-functional down-selection of equipment, tooling, and process parameters with Development, Equipment, Quality, and Production counterparts

• Partner with product design to translate design constraints into realistic process requirements and how to strategically absorb product changes without sacrificing yield or cycle time

• Drive design specifications, design reviews, and buy-off criteria for automation equipment that performs dispense (adhesives, potting, sealants, form-in-place gaskets, and related structural joining)

• Leverage data driven decision making to root-cause production issues and drive the optimal outcome

• Optimize deployed processes to hit yield, quality, and cycle time targets; own process capability and control through ramp

• Build and maintain the factory process knowledge base: standards, work instructions, PFMEA/control plans, and lessons learned from launch and production

What You’ll Bring

• 5+ years of engineering, or equivalent relevant experience, with demonstrated ownership of high-volume manufacturing processes

• Hands-on experience deploying and sustaining dispense and structural joining processes at volume (adhesives, potting, sealants, form-in-place gaskets, curing), including product interfaces, materials, process windows, and automation equipment

• Experience writing equipment specifications, running design reviews, and accepting automation that must meet process capability, quality, and cycle time requirements

• Proven root-cause and process-optimization skill: yield loss, cycle time, and production issues closed with designed experiments, capability data, and line-side problem solving

• Proficiency in Geometric Dimensioning & Tolerancing (GD&T) and experimental design

• Degree in Engineering, or equivalent experience