Solutions Data Engineer• Architect, develop, and test large scale data solutions, to provide efficient analytical and reporting capabilities across Apple’s supply chain teams. • Develop highly scalable data pipelines to load data from various source systems, use Apache Airflow to orchestrate, schedule and monitor the workflows. • Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear.• Ensure data quality through setting up data quality management frameworks and anomaly detection capabilities. • Communicate the results and insights effectively to partners and senior leaders, providing clear and actionable recommendationsSoftware Engineer• Develop user-friendly and intuitive web or native (macOS/iOS) client-server applications • Experienced in interfacing with APIs from a variety of sources• Additional ability to write backend endpoints in the application backend to serve client code (Golang preferred)• Ability to implement UI/UX designs into an application• Skilled in writing SQL queries• Experience integrating applications with ML models, a plus• Write clean, modular, robust code to implement features with no supervision • Quickly prototype new ideas to collect user feedback• Solve complex problems in a fast paced, iterative, and multi-release environment • Ensure robust security and access control in software applications • Introduce automation into build processes • Distill fuzzy business needs into software features through in-depth conversation with non-technical users and leadership • Take lead on building strong relationships within Apple, structuring valuable discussions around user experience/challenges, and turning insights into solutions • Possess a strong customer focus and be eager to work with business partners Machine Learning Engineer• Apply your AI/ML expertise to develop models for applications like predictive analytics, recommendation systems, and anomaly detection, enhancing search functionality and user experience.• Build, train, and fine-tune deep learning models to understand natural language queries, rank results, and improve retrieval accuracy across large-scale data.• Develop and optimize NLP-based search engines using semantic search techniques and transformers, such as BERT, to enhance relevance and precision of search results.• Leverage NLP techniques such as entity recognition, intent classification, and semantic matching to interpret and process search queries effectively.• Work closely with product managers, data scientists, and engineering teams to integrate models into production systems, ensuring they meet business needs.• Continuously evaluate and optimize models for accuracy, efficiency, and scalability, focusing on reducing latency in search results and improving relevance.• Stay up-to-date with the latest advancements in AI/ML, NLP, and search technologies to innovate and enhance our products.