苹果Automation Engineer – Machine Learning

The Infrastructure Systems Engineer will do the following tasks, through collaboration with team members in China and around the world. - Analyze the requirements, demands, constraints and challenges of machine learning in local or global environments, design or re-design platform architecture to improve its scalability and agility, and to enable new, high-impact use cases - Develop and implement the above design, bringing it to an internal product, with observability to support efficient system management - Design and/or enhance automation of operations for infrastructure and platforms, including tools and processes of monitoring, logging and alerting, to improve scalability in both system construction and runtime operations - Support Dev and Eng efforts through provisioning operational solutions, co-design ML application architecture and drive the coordination among local and global, internal and cross-functional groups to achieve the result of success - Create performance profile for platforms and services, defining service level objectives (SLO) and driving the measurement, monitoring and evaluation over these objectives - Lead constant evaluation on system performance and reliability, discover potential faults, drive RCA and fixes

The Infrastructure Systems Engineer will do the following tasks, through collaboration with team members in China and around the world. - Analyze the requirements, demands, constraints and challenges of machine learning in local or global environments, design or re-design platform architecture to improve its scalability and agility, and to enable new, high-impact use cases - Develop and implement the above design, bringing it to an internal product, with observability to support efficient system management - Design and/or enhance automation of operations for infrastructure and platforms, including tools and processes of monitoring, logging and alerting, to improve scalability in both system construction and runtime operations - Support Dev and Eng efforts through provisioning operational solutions, co-design ML application architecture and drive the coordination among local and global, internal and cross-functional groups to achieve the result of success - Create performance profile for platforms and services, defining service level objectives (SLO) and driving the measurement, monitoring and evaluation over these objectives - Lead constant evaluation on system performance and reliability, discover potential faults, drive RCA and fixes

About TI As a global semiconductor company, we design, manufacture, test and sell analog and embedded processing chips to nearly 100,000 customers. Our products enable electronics everywhere and in things you experience every day - from health care, smart homes and connected cars to drones, smart phones and more. Our passion to create a better and more sustainable world by making electronics more affordable through semiconductors drives us to make our technology smaller, more efficient, more reliable and more affordable. About the Job The AI Engineer will drive implementation of artificial intelligence and machine learning solutions to enhance semiconductor back-end manufacturing operations. The role will involve close collaboration with manufacturing teams, data scientists, product and process engineers to identify opportunities and implement AI-driven solutions that improve operational efficiency, quality, and yield. This position requires a strong understanding of AI/ML technologies, experience with semiconductor manufacturing, and a passion for applying data-driven techniques to solve complex industrial problems. Responsibilities include: • Collaborate with cross-functional teams and domain experts to identify opportunities for AI integration in workflows. • Analyze and preprocess large datasets from manufacturing equipment, sensors, and logs to enable effective machine learning applications. • Lead proof-of-concept projects and pilot programs to demonstrate the value of AI applications in manufacturing settings. • Develop and deploy AI/ML models for defect detection, yield improvement, process optimization, and predictive maintenance in semiconductor back-end manufacturing processes. • Provide technical documentation, training, and support to ensure seamless adoption of AI solutions by production teams. • Monitor AI systems performance and implement enhancement. Stay updated with the latest advancements in AI/ML and propose innovative solutions applicable to semiconductor manufacturing.

You will join a dynamic team focusing on improving the cellular stability and performance of the latest iPhone/iPad/Watch. Your job responsibilities will include but not limited to below points: - Leveraging artificial intelligence (AI) technologies to execute 5G/4G cellular test jobs, analyze test results to identify in-depth and potential stability and KPI issues, generate analysis reports, and provide data-driven insights for problem resolution. - Developing natural language-based Chatbot tools tailored to the team's needs, enabling efficient information retrieval, test-related consultation, and automated interaction in the cellular stability testing workflow. - Applying AI methods to optimize the team's test strategies, test cases, and related processes for cellular stability testing, enhancing test coverage, accuracy, and resource utilization.