Machine Learning Engineer (Applied AI)

Summary Posted: Aug 23, 2024 Weekly Hours: 40 Role Number: 200558344 We are looking for an experienced Machine Learning Engineer to help us 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. You will lead all the processes from requirement analysis, data collection, cleaning, and preprocessing, to training models and deploying them to production. Description Description As a Machine Learning Engineer in Manufacturing Design team, you will have the opportunity to work with all the line of business on Apple’s hero products. You'll contribute to deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark. In this role you will: - Collaborate with business teams to analyze key business problems and develop innovative ML solutions - 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 - Monitor and maintain deployed models to ensure they continue delivering value - Connect with other AI/ML teams within Apple and be a trusted advisor for the ML knowledge and experience Minimum Qualifications Minimum Qualifications Master or PhD or equivalent experience in Computer Science, Machine Learning, Statistics, Operations Research, Mathematics, Engineering, or a related field with a minimum of 3 years’ experience applying machine learning to solve real-world business challenges Demonstrated strong experience on problem definition, can transform business problems into ML solutions very well Experienced in building, deploying and running Machine Learning applications or services Demonstrated expertise in machine learning, deep learning, or reinforcement learning Proficiency in implementing data-intensive pipelines and applications using programming languages such as Python, Java or Golang Strong written and verbal communication skills Key Qualifications Key Qualifications Preferred Qualifications Preferred Qualifications Practical experience in at least one of the following domains: time series forecasting, anomaly detection, search and recommendation systems, feedback control, or computer vision Hands-on experience working with deep learning toolkits such as Scikit-Learn, AutoGluon, PyTorch or TensorFlow Experience in programming with a language such as Python, Java or Golang. Experience with SQL and database systems such as PostgreSQL. Experience with building ETL pipeline in data warehouse such as Snowflake Education & Experience Education & Experience Additional Requirements Additional Requirements More