Manufacturing Design & Manufacturing Quality Engineer
Confirmed on the employer's own hiring board on Oct 26, 2026. First seen by Alion on Aug 5, 2026. Apple scores A on the Alion truth index.
Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. The people here don’t just build products - they craft the kind of wonder that’s revolutionized entire industries. Bring passion and dedication to your job and there's no telling what you could accomplish.
Join the Manufacturing Design (MDE) and Quality Engineering (MQE) teams, and help enable the mass creation of impossible products as a partner in the development of Apple's renowned designs.
Description
In this highly visible new graduate role, you will have the opportunity to make a significant impact on Apple products and leave a footprint for years to come. You will apply your engineering background to evaluate product designs, develop cutting-edge manufacturing methods, and implement rigorous quality controls.
Whether your academic or project background lies in mechanical fabrication, materials science, automation, or data-driven analysis, you will bridge foundational engineering principles with high-volume manufacturing to achieve ambitious specifications at a massive scale. Both MDE and MQE tracks will require close collaboration with Asia-based manufacturing partners to support on-site prototype builds, equipment testing, and factory ramp-ups.
Minimum Qualifications
BS or MS in Mechanical Engineering, Automation, Mechatronics, Materials Science, Industrial Engineering, or a related technical discipline.
Academic lab, or internship involvement focusing on at least one of the following domains: CNC, laser processing, 3D printing, automation, assembly, materials, surface treatments, Failure Analysis (FA), or data science.
Preferred Qualifications
Solid grasp of engineering fundamentals, 2D/3D design, measurement technologies, and core manufacturing processes.
Track record of conducting root cause analysis or evaluating data using statistical analysis tools (e.g., JMP, Minitab) for process optimization.
Foundational programming skills (e.g., Python, MATLAB) with exposure to automation control methodologies, computer vision, or machine learning.
High self-motivation combined with a highly detail-oriented and results-driven approach to solving hands-on engineering problems.
Demonstrated ability to communicate complex technical concepts effectively to multi-functional teams.