Manufacturing Design Engineering Intern

Summary

Posted: Dec 24, 2024
Weekly Hours: 40
Role Number:200570780

Apple is a place where extraordinary people gather to do their best work. Just be ready to dream big. Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. We provide equal opportunities. The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. The Apple Manufacturing Design Engineer (MDE) is accountable for driving the development of key mechanical manufacturing processes across Apple’s worldwide supply base. In this highly visible, hands-on role as the expert technical member of the Manufacturing Design Team you will have direct frequent communication and collaboration with Apple Industrial Design, Product Design, Manufacturing Design partners and worldwide suppliers.

Description

We're looking for talents for either one of below directions: Direction 1: Engineers that provide end to end manufacturing and process solutions for key design features. This includes manufacturing process development and capability (all aspects of equipment, consumables, key parameters etc ) selection, and/or design of manufacturing equipment, automation, and strategic R&D. - Design and optimize glass manufacturing process, including Laser, CNC, Polishing, Chemical Etching, Chemical Strengthening, Decoration - Trouble shooting on engineering problems and use data to drive process decisions with data analysis, DOEs, SPC, etc. - Collaborating cross functionally with various departments(Tooling, Product Design, Quality, Subject Matter Expert, Global Supply Manager) and coordinating activities through clear communication between the Asia and US based teams, as well as suppliers. OR Direction 2: Experienced Machine Learning Engineer to help extract value from manufacturing data and apply the AI/ML technologies (e.g. classification, regression via structured data and image data) into the real-world production. Lead all the processes from requirement analysis, data collection, cleaning, and preprocessing, to training models and deploying them into production. - Collaborate with process/factory teams to analyze key engineering problems and develop innovative ML solutions to the problems. - Design advanced machine learning models that solve real-world problems and validate ML solutions end-to-end - Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready - Connect with other AI/ML teams within Apple or within suppliers and be manufacturing team advisor for the ML application.

Minimum Qualifications

• We're looking for talents who can meet either one of below requirements:
• Demonstrate hands-on mechanical ability
• Ability to work in team-based environment
• Strong written and verbal interpersonal skills in English.
• Strong motivation, curiosity, passion, creativity
• Computer aided design (CAD) skills: 3D CAD experience required (Abaqus, Ansys, NX preferred)
• Basic engineering skills: tolerances analysis, design for assembly (DFA), design for manufacturing (DFM), simple fixture design, understanding of Statistical Process Controls (SPC), understanding of metrology (basic knowledge of measurement systems)
• Able to be based in Changsha or Shenzhen
• Minimum > 6 months full time for internship projects.
• 2nd or 3rd year in MS or PhD in mechanical, manufacturing, or data science related preferred

Preferred Qualifications

• Experience: Machine Learning, Computer Science, Data Science, Statistics or related areas
• In-depth knowledge in deep learning (DL) and statistical machine learning (ML).
• Practical experience in at least one of the following domains: time series forecasting, anomaly detection, search and recommendation systems, feedback control, interpretable machine learning or computer vision
• Proficiency in programming languages like Python.
• Experience working on Linux and macOS based platforms
• Hands-on experience working with deep learning toolkits such as Scikit-Learn, AutoGluon, PyTorch or TensorFlow
• Demonstrated ability to conduct innovative research and publish findings in top-tier conferences and journals.
• Excellent presentation skills.