AMDAI/ML Design Engineer Intern

As an intern, you will: Design and prototype AI-driven tools that support hardware engineers in data analysis, test automation, and debugging workflows. Implement backend services in Python and frontend interfaces in TypeScript (React/Next.js). Integrate databases (SQL, vector databases) for data storage, search, and retrieval. Explore AI/ML workflows (embeddings, retrieval, summarization, code assistance). Collaborate with hardware and software engineers to translate requirements into working tools. Write clear documentation, tests, and deployment scripts.

As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state-of-the-art research in ML to tackle complex data problems. The solutions you develop will significantly impact future Apple products and the broader ML development ecosystem. You will work with a multidisciplinary team to actively participate in the data-model co-design and co-development practice. Your responsibilities will extend to the design and development of a comprehensive data curation framework. You will also create robust model evaluation pipelines, integral to the continuous improvement and assessment of ML models. Additionally, your role will entail an in-depth analysis of collected data to underscore its influence on model performance. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues. Your work may span a variety of topics, including but not limited to: * Designing and implementing semi-supervised, self-supervised representation learning techniques for maximizing the power of both limited labeled data and large-scale unlabeled data. * Developing evaluation protocols centered on the end-to-end user experience, with a focus on anticipating potential failure modes, edge cases, and anomalies. * Employing data selection techniques such as novelty detection, active learning, and core-set selection for diverse data types like images, 3D models, natural language, and audio. * Uncovering patterns in data, setting performance targets, and leveraging modern statistical and ML-based methods to model data distributions. This will aid in reducing redundancy and addressing out-of-distribution samples.

• Execute AI/ML projects, including developing domain-specific chatbots for wireless testing reports (from internal teams and third-party labs), as well as regulatory and standards documents from global authorities. • Research and apply innovative LLM techniques, such as workflow optimization, model architecture design, and prompt engineering, to improve efficiency and accuracy. • Perform data mining, analysis, and predictive modeling using advanced ML approaches to generate actionable insights. • Design, develop, and maintain web applications (front-end and back-end) to support AI/ML tools and data visualization. • Deploy, optimize, and maintain softwares and models in production environments, ensuring scalability, reliability, and performance.

• Cooperate with cross functional and multidisciplinary teams to specify camera FMEA risk, develop and deploy calibration and performance validations stations to reduce camera product risks throughout the NPI cycle • Work with equipment vendors to design the perfect equipment from scratch for calibrating and verifying the performance of Apple products • Specify and acquire instruments, components and tools for use in an NPI environment • Run simulations or experiments to make data driven decisions and present results to senior management • Design, develop, debug and optimize algorithms to meet with accuracy and precision requirement for camera calibration and performance verification • Generate reports that analyze large amounts of NPI camera performance data, and present at both working level and executive level meetings • Up to 10% domestic and international traveling