苹果Machine Learning Engineer - Intern
任职要求
Minimum Qualifications • Currently pursuing a PhD degree or equivalent experience in Machine Learning, Computer Vision, Natural Language Processing, Data Science, Statistics or related areas. • Proven expertise in machine learning with a passion for data-centric machine learning. • Experience with natural language processing (NLP), and large language models, such as BERT, GPT, or Transformers. • …
工作职责
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.
Responsibilities Responsible for the architecture design and development of the e-commerce search system, ensuring high performance, scalability, and reliability. Explore and apply cutting-edge technologies in Natural Language Processing (NLP), Deep Learning, and Generative AI to improve search relevance, precision, and recall. Responsible for the design and development of retrieval, machine learning, and data pipeline architectures, including indexing, feature engineering, model training, big data processing, and streaming computation components.
• Candidate will be responsible for: • - Collaborate with senior engineers to design and develop ML tools for data processing, analysis, and visualization. • - Integrate and validate machine learning models on Apple new product introduction (NPI) process and mass production. • - Develop and implement automated pipelines for model training and evaluation. • - Conduct experiments to evaluate the effectiveness of different models and algorithms. • - Participate in code reviews, testing, and documentation to ensure high-quality and maintainable code. • - Keep up-to-date with the latest advancements in machine learning and data science techniques.
We are seeking a motivated Machine Learning Engineer Intern to join our autonomous vehicle research and development team. The intern will assist in building, training, and optimizing machine learning models that enable real-time perception, decision-making, and control for self-driving vehicles. What you’ll be doing: • Develop and test deep learning models for object detection, tracking, and behavior prediction. • Preprocess and analyze sensor data from LiDAR, radar, and camera systems. • Collaborate with cross-functional teams on algorithm integration and performance evaluation. • Support data labeling, simulation, and validation pipelines. • Document model performance and contribute to internal reports.
• The Infrastructure Systems Engineer Intern 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 platform 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 • - Investigate new technologies to enhance system performance, reliability and redundancy. Create performance profile for platforms and services, defining service level objectives (SLO) and driving the measurement, monitoring and evaluation over these objectives • - Improve 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 • - Develop and implement the above design, bringing it to an internal product, with observability to support efficient systems management