Job Information
Apple Industrial Machine Learning Engineer in Cupertino, California
Weekly Hours: 40
Role Number: 200635247-0836
Summary
Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. 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. Our team is responsible for the development of the inspection equipment that determines if a product meets Apple's high standards across all of the mechanical portion of hardware we make - iPhone, Mac, iPad, Watch and others.
Description
- Collaborate with mechanical and quality engineers to apply machine learning and computer vision to industrial problems and manufacturing situations
- Develop and deploy ML models for inspection equipment responsible for judging millions of units per day in challenging production environments
- Identify opportunities in production and development processes to apply machine learning tools for improvements
- Develop toolkits to guide application of machine learning combined with statistical tools for engineers
- Assemble and analyze large data sets through SQL-based querying or development of scripts and code-modules to collate distributed and disparate data sources
- Apply pattern detection and anomaly identification techniques to measures of interest Proof-of-concept application of ML methods, Neural Networks, and Computer Vision for prescriptive/predictive applications
- Develop software components in Python, Java, and/or C/C++/Obj-C towards roll-out of data automation systems
- Work with 2D/3D triangulation laser systems and/or CCD inspection systems (Halcon, Keyence, Cognex, Visco)
- Balance technical requirements while effectively managing collaborations with vendors to maintain schedule and ramp dates
- Occasionally wear multiple hats: technical project manager, database specialist, and optics improvement specialist
Minimum Qualifications
12+ years of solid hands-on experience applying machine learning and/or computer vision techniques to build models integrated into industrial/manufacturing applications
Experience with image processing and using ML tools to identify patterns in images, specifically applied to industrial or manufacturing environments
Experienced user of machine learning and statistical-analysis libraries such as GraphLab Create, Turi Create, scikit-learn, scipy, PyTorch, Keras, NetworkX, Spacy, and NLTK
Strong software development skills with proficiency in Python
Strong working knowledge of ML algorithms including decision trees, probability networks, association rules, clustering, regression, neural networks, CNNs, and object detection
Familiarity with mechanical metrology system qualification processes (GRR, Correlation, Stability, Reliability)
Basic understanding of manufacturing processes (CNC, modeling, laser welding, etc.)
Ability to explain and present analyses and machine learning concepts to a broad technical audience
Ability to travel internationally to manufacturing sites – 25-50%
Preferred Qualifications
Experience with deep learning frameworks such as mxnet, Torch, Caffe, and TensorFlow
Experience with cloud computing platforms (AWS) and deployment tools like Docker
Experience building Software ML solutions from inception to production
Proficiency with CLI, Linux and Unix shell scripting
Data visualization, data analytics, and data mining experience
International team leadership experience (academic or professional)
Knowledge of basic networking concepts and protocols (TCP/IP, HTTP, etc.)
Understanding of optics, image acquisition, software filtering and judgment algorithms
Intermediate knowledge of automation including system layout, architecture, and cycle time optimization
Proven track record for self-study and self-exploration into new tools and techniques
Ability to analyze existing database schema DDL/instance layout and determine migration impacts
Strong interest in technical details while maintaining grasp of the big picture as it relates to overall product quality
High level of autonomy and influence to unblock delivery of results across various teams
Applied background in Hadoop, Spark, Hive, Cassandra, and knowledge of R is a plus
Strong analytic problem-solving skills and aptitude for learning systems quickly
Creative collaboration skills
Proficient use of English both written and oral
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .