INFORMS - Intern (ML Engineer, Data Quality Lead and Capacity PM)
Santa Clara Valley (Cupertino), California, United States
Machine Learning and AI
Manufacturing Systems and Infrastructure – iPhone Operations Machine Learning Engineer, Data Quality Lead and Capacity Planning Program Manager Imagine what you could do here. At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Every single day, people do amazing things at Apple. Do you want to impact the future at Apple by developing an extraordinary platform for our Operations team? Apple is a data-centric company where many critical decisions are made based on data. The completeness, accuracy and timeliness of data has huge implication to our decision-making. Every shipped Apple product undergoes rigorous testing at our factories to ensure the best customer experience. Our team handles the collection and reporting of all manufacturing data. Machine Learning Engineer Through the use of statistics, the scientific process, and machine learning, the team recommends and implements solutions to the most challenging problems. We’re looking for experienced machine learning professionals to help us revolutionize how we manufacture Apple’s amazing products. Put your experience to work in this highly visible role. Key responsibilities • Collaborate with robotics, automation specialists, manufacturing and product development engineers to apply machine learning to industrial problems and situations • Seek opportunities in the production and development processes to utilize deep learning, algorithms and other ML tools for improvements • Implementation of ML tools, such as Neural Networks for a wide range of prescriptive/predictive applications in dynamic production environments • Develop software in Python, R and/or C/C++/Objective-C towards roll-out of a data automation system Qualifications • Hands-on experience with design, implementation and application of ML/AI/Deep Learning solutions and techniques to build models that solve real problems. • Strong software development skills with proficiency in Python • Experience with image processing, Computer Vision, and using ML tools to identify patterns in images. Specifically applied to industrial or manufacturing environments is a nice to have. • Experience applying deep learning frameworks, such as PyTorch/Torch, Caffe2, TensorFlow, Keras, Theano to real world applications that solve problems • Experienced user of machine learning and statistical-analysis libraries, such as GraphLab Create, scikit-learn, scipy, NetworkX, Spacy, and NLTK Data Quality Lead We are looking for a Data Quality Lead to manage centralized data management and ensure data completeness and accuracy across product lines. You will be diving into data forensics, maintain the integrity of data through root cause analysis and improving solutions for end-to-end data flow. This is an excellent opportunity if you are looking to make a big impact. Responsibilities • Engage with product, test and assembly teams to understand product data needs • Understand and articulate implications of factory processes on data completeness and accuracy • Design data quality plan and drive cross-functional support for implementation • Set up processes to automatically detect data quality issues • Root cause data issues and drive corrective actions with Contract Manufacturers, Suppliers and each of the Lines of Business. Qualifications • Experience with Data Quality initiatives (data profiling, improvement, accuracy, completeness, data integrity, data stewardship, and data governance) • SQL experience writing queries within large-scale databases • Unix experience (shell scripting, grep, find, etc..) • Big Data experience in accessing and running scripts against Hive, Druid, Hbase is an Capacity Planning Program Manager The Capacity PM will gather requirements, develop simulations, and communicate build plans to cross-functional teams and executive management. Build plans will be generated through internal simulations or by working directly with OEM partners. Responsibilities • Developing a unified format and logic between sites and vendors for long-term capacity. • Working with product operations and engineering to define criteria used for simulations. • Capacity modeling for all sites. Focus would be long-term capacity to simulate EOL (end of life) transitions and new product ramps to ensure seamless transition between programs. • Developing long-term site strategies with supply demand management and materials Requirements • Data analytics — taking tons of data and helping build out or select tools to analyze production, capacity, lead times, cost structures, etc. • Data modeling, simulations or optimization tools like Gurobi, Cplex or Xpress • Programming experience with Java, C++, Python or Perl • Excellent communication skills, both verbal and written
- Hands-on experience with design, implementation and application of solutions and techniques to build models that solve real problems. Strong software development skills.
• Collaborate with robotics, automation specialists, manufacturing and product development engineers to apply machine learning to industrial problems and situations • Seek opportunities in the production and development processes to utilize deep learning, algorithms and other ML tools for improvements • Analyze huge amounts of data-identifying anomalies (pattern detection) and variabilities in a measure of interest
Education & Experience
BS in Engineering or Supply Chain or equivalent degree. Masters degree or PhD is considered a plus.