In this role, you will collaborate with wireless software engineering teams to develop and integrate AI-powered -cellular performance analysis tools, to detect radio link failures, protocol inefficiencies and performance bottlenecks. As a Machine Learning Engineer, you will be responsible to design and develop cutting-edge ML models tailored for deep analysis of cellular logs from various sources like lab, field, QA tests, apply deep learning and reinforcement learning techniques to improve modem-level diagnostics and enhance performance optimization, use pattern AI-driven recognition and anomaly detection to uncover hidden issues impacting wireless connectivity. Along with application of 4G/5G domain knowledge for the development of advance ML models for deep analysis, you will be working cross-functionally with platform architecture, standardization, firmware/protocol development, system test, Field Test, QA and carrier engineering teams to drive the enhancement proposals from concept to commercialisation. As part of this team, you will impact the iPhone, iPad and Apple Watch user experiences worldwide. Proven experience in applying machine learning algorithms (and familiarity with ML libraries like TensorFlow, PyTorch, Scikit-learn, etc.) to understand real-world data, in particular for cellular technologies. Demonstrated programming skills in Python for ML model development and log processing. Good understanding of 3GPP standards(4G/5G) and cellular communications systems and technologies. Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, AI, or related fields. Knowledge of cloud-based ML deployment for large-scale modem log analysis. Solid understanding of 5G and LTE PHY/MAC/Protocol stack, TCP/IP Experience in modem log analysis, protocol stack debugging or Cellular SW development is a great plus. Thrive in a collaborative environment and can clearly communicate while expertly driving multiple projects across many teams. Obsessively passionate and inquisitive, and seek to solve everyday problems in innovative ways. Strong analytical, result oriented, problem-solving approach with a laser-focus on the smallest details that are meaningful to our customers. Excellent debugging skills along with good interpersonal, communication, and presentation skills