亚马逊Sr. Audio Algorithm Software Engineer, Asia Tech Center

In your lead role you will be the owner of all aspects of EE hardware design including, circuit/board design and validation. As part of a system team, you will work alongside system integrator and technology focused engineers who are subject matter experts of their fields. You will be responsible for integrating various core features of the product such as mics, speakers, display, cameras, and sensors, improving overall system quality, working with software/product design engineers to optimize product performance, and debugging complex systemic problems. You will be involved in projects from concept through production, gaining exposure to the complete design lifecycle. You will also support engineering builds gaining experience with high volume manufacturing.

As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying innovative research in foundation models to with a particular focus on audio data. This includes working across the full ML pipeline—from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning with task-specific datasets. The solutions you develop will have a significant impact on future Apple software and hardware products, as well as the broader ML ecosystem. Your responsibilities will extend to designing and developing a comprehensive multi-modal data generation and curation framework for foundation models at Apple. You will also contribute to building robust model evaluation pipelines that support continuous improvement and performance assessment. In addition, the role involves analyzing multi-modal data to better understand its influence on model behavior and outcomes. 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: Designing self-supervised and semi-supervised representation learning pipelines, and fine-tuning strategies for tasks like speech recognition and speaker identification. Applying data selection techniques such as novelty detection and active learning across multi modalities to improve data efficiency and reduce distributional gaps. Modeling data distributions using ML/statistical methods to uncover patterns, reduce redundancy, and handle out-of-distribution challenges. Rapidly learning new methods and domains as needed, and guiding product teams in selecting effective ML solutions.

As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying innovative research in foundation models to with a particular focus on audio data. This includes working across the full ML pipeline—from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning with task-specific datasets. The solutions you develop will have a significant impact on future Apple software and hardware products, as well as the broader ML ecosystem. Your responsibilities will extend to designing and developing a comprehensive multi-modal data generation and curation framework for foundation models at Apple. You will also contribute to building robust model evaluation pipelines that support continuous improvement and performance assessment. In addition, the role involves analyzing multi-modal data to better understand its influence on model behavior and outcomes. 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: Designing self-supervised and semi-supervised representation learning pipelines, and fine-tuning strategies for tasks like speech recognition and speaker identification. Applying data selection techniques such as novelty detection and active learning across multi modalities to improve data efficiency and reduce distributional gaps. Modeling data distributions using ML/statistical methods to uncover patterns, reduce redundancy, and handle out-of-distribution challenges. Rapidly learning new methods and domains as needed, and guiding product teams in selecting effective ML solutions.

职责和责任： 我们正在寻找一位高级c++开发工程师，为腾讯海外游戏工作室设计和开发云上的创新服务/解决方案 我们的内部客户包括内部客户或收购游戏工作室。工作范围包括了解客户的业务需求、收集技术需求、基于领先的行业最佳实践开发参考架构和原型、领导全球各地的实施和部署，以及必要时的问题解决 我们正在寻找的人： 主观能动、自主性、执行力、学习能力强，并具有团队精神 自驱力强，善于表达，充满激情 拥有协作、独立、坚持、灵活和开放精神 以客户为导向 Work Location: China-Shanghai