苹果Machine Learning Engineer
任职要求
Minimum Qualifications • Communication & Presentation: Superior verbal and written communication and presentation skills, ability to convey meticulous mathematical concepts and considerations to non-experts. • Machine Learning: Understanding of common machine/deep learning algorithms and practical experience in one or more of the following areas: time series forecasting, anomaly detection, convex optimization, computer vision, NLP, LLM, recommendation system and Auto ML • Databases: Solid understanding of relational databases, including SQL, an…
工作职责
Collaborate & Innovate – Work closely with cross-functional teams to identify opportunities, gather requirements, and transform challenges into scalable technical solutions. Design Advanced Models – Develop state-of-the-art data science and machine learning approaches, leveraging proven methodologies or creating custom algorithms tailored to business needs. Build Robust Systems – Partner with data engineers and platform architects to implement high-performance, real-time and batch decisioning solutions. Communicate Insights – Present findings to business stakeholders and executives, ensuring data-driven strategies translate into meaningful business outcomes. Explore & Evolve – Stay at the forefront of technological advancements by researching new techniques across data science, engineering, and visualization to continuously refine the team’s capabilities.
Job Description： 1.Optimize the recommendation quality and user profile in Mi.com website, provide users the best shopping experience； 2.Combine your understanding of product objectives and take full advantage of modern machine learning, NLP and Multimodal techniques to improve the recommendation result metrics； 3.Work with products and DAs, and other engineers to deliver features to drive the experience optimization of products.
• 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.
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.
The computer vision algorithm engineer will work in a dynamic team as part of the Video Computer Vision org. which develops on-device computer vision and machine perception technologies across Apple’s products. We balance research and product to deliver the highest quality, state-of-the-art experiences, innovating through the full stack, and partnering with cross-functional teams to influence what brings our vision to life and into customers hands.