职位描述：
Summary：
As part of Apple’s AI and Machine Learning org, we inspire and create groundbreaking technology for multi-modal models with strong agent and reasoning capabilities. The Data and Machine Learning Innovation (DMLI) team is seeking a passionate Machine Learning Engineer to explore new methods, challenge existing metrics and protocols, and develop new insightful practices that will change how we understand data and overcome real-world ML challenges. As a team member, you will work on some of the most ambitious technical challenges in the field. Your role will involve collaborating closely with our team of machine learning researchers, engineers, and data scientists. Together, you will spearhead groundbreaking research initiatives and develop transformative products designed to create a significant impact for billions of users worldwide.
Description：
As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state-of-the-art research in foundation models to tackle complex data problems. The solutions you develop will significantly impact future Apple software and hardware 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 designing and developing a comprehensive data generation and curation framework for foundation models at Apple. You will also be responsible for creating robust model evaluation pipelines, integral to the continuous improvement and assessment of foundation models. Additionally, your role will entail an in-depth analysis of multi-modal data to understand 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 various applications, including:
– Enhancing current products and future hardware platforms with multi-modal perception data.
– Designing and implementing semi-supervised, self-supervised representation learning techniques to maximize the power of both limited labeled data and large-scale unlabeled data.
– Developing on-device intelligence and learning with strong privacy protections.
– 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.
– Learning new skills rapidly and applying them as needed, e.g., learning a new machine learning algorithm from a research paper and implementing it; mastering basic knowledge from a new domain in a short amount of time.
– Providing technical guidance to product teams on choosing appropriate machine learning approaches for tasks.
职位要求：
Minimum Qualifications：
Deep technical skills in one or more machine learning areas, such as computer vision, combinatorial optimization, causality analysis, natural language processing, and deep learning.
Strong software development skills with proficiency in Python; hands-on experience working with deep learning toolkits like PyTorch, TensorFlow, or JAX.
5+ years of experience developing and evaluating ML applications, demonstrating a passion for understanding and improving model/data quality.
Preferred Qualifications：
Deep understanding of multi-modal foundation models.
Staying up-to-date with emerging trends in generative AI and multi-modal LLMs.
The ability to formulate machine learning problems, design, experiment, implement, and communicate solutions effectively.
Hands-on mentality to own engineering projects from inception to shipping products and the ability to work independently and as part of a cross-functional team.
Demonstrated publication records in relevant conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.).
Track records of adopting ML to solve cross-disciplinary problems.
招聘部门：
Apple Machine Learning and AI
工作地点：
Beijing, Beijing, China
面试建议：
Apple的这个机器学习工程师职位非常注重在多模态基础模型和数据创新方面的能力。面试官会特别关注你在基础模型研究、数据生成框架设计以及模型评估方面的实际经验。这个职位不仅要求扎实的机器学习技术功底，还需要具备快速学习新领域知识的能力，以及将研究成果转化为实际产品的能力。 准备面试时，你需要重点准备以下几个方面：首先，深入理解多模态学习的最新进展，特别是与Apple产品可能相关的应用场景。其次，准备好展示你在数据生成和模型评估方面的项目经验，最好能提供具体的案例和量化结果。第三，由于这个职位强调创新，你需要准备一些你如何挑战现有方法、提出新思路的例子。最后，不要忽视沟通能力的展示，这个职位需要与跨职能团队紧密合作，因此清晰表达技术概念的能力同样重要。建议提前复习PyTorch/TensorFlow的实战经验，并准备1-2个你解决过的具有挑战性的ML问题。
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