苹果AIML - Sr. Machine Learning Engineer - Data and ML Innovation
任职要求
Minimum Qualifications • Deep technical skills in one or more machine learning areas, such as computer vision, audio, 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 (one of). • 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 with multi-functional teams. • 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.
工作职责
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.
The Role As a Software Product Engineer of IT Sales applications, you will be responsible for leading a wide variety of cross-functional programs across sales and customer experience application,system integration, server systems, and diagnostics. In this role, you will lead the design and development of some of the most advanced and sophisticated systems in the world, with unparalleled agility. Responsibilities • Design the new functionalities in applications to support the growth of our sales. • Work with US IT team to implement global rollout to China with local gap prioritized. • Manage the implementation as project manager. • Manage cross-functional software programs from end-to-end. • Develop and manage project plans and ensure on-time delivery. • Work closely with engineering teams to effectively coordinate complex design inter-dependencies. • Constantly work to evolve our processes towards increasing precision and dependability, while still maintaining the agility that has gotten Tesla to where we are now. • Work with the UX, dev, and QA teams with strength and confidence through rapid development cycles, changing requirements, and uncertainty. • As business partner to manage IT requirements of specific domain.
Every day will bring new and exciting challenges on the job while you: - Act as a strategic advisor for customers' Generative AI initiatives and internal AI agent innovation - Drive the development and implementation of collaborative AI agents within the TAM organization - Lead technical discussions around AWS AI services including Bedrock, Claude, and Amazon Q. - Make recommendations on AI architecture, security, cost optimization, and operational excellence - Champion internal AI agent success stories to inspire customer innovation - Complete analysis and present periodic reviews of AI workload performance - Guide customers in developing responsible AI practices while ensuring security and compliance - Foster an ecosystem where AI and humans progress together through knowledge sharing - Work with AWS AI/ML service teams to advocate for customer needs - Participate in customer requested meetings (onsite or via phone) - Work directly with Amazon Web Service engineers to ensure rapid resolution of AI-related issues - Available in non-business hours to handle urgent issues ------------------------------------------------
Sr. Product Marketing Manager( AI/ML) Amazon Web Services , a subsidiary of Amazon.com, is seeking a talented Product Marketing Manager for driving data-driven products in the cloud computing adaption journey with Internet companies, Enterprise, Startups, and Developer communities’ area in China. This is a unique opportunity to play a key role in an exciting, industry-leading technology business. Product marketing is the critical role of acting as the Voice of the Customer to the company, communicating the product value to the market. The inherent business demand of this position is to drive customer engagement, facilitate marketing program along with the product lifecycle. The Product Marketing Manager is a not only technical but also strategic position. The position will be a key driver who can drive the data-driven services adoption of internet companies, traditional Enterprise, Startups, Developer communities’ IT environment. It means the position needs to have the ability to communicate with IT professionals, business executives, developers, IT Ops and data scientist/ data engineers. In addition, the product marketing manager needs deep understanding of cloud computing technologies, particularly database, big data, AI/ML, IoT. Since the pace of innovation of cloud computing is so quick, the person should be willing to catch up with new technologies and use-cases proactively. Role and Responsibilities • Design and Deploy the AWS Generative AI go-to-market(GTM) strategy into marketing programs to accelerate the service adoption • Drive and lead new service launch programs to strengthen AWS thought leadership and technology awareness • Developing marketing tools and campaign assets to attract new prospect and customers to generate product demands and marketing leads • Build and strengthen the influencers’ community to generate businesses in the Enterprise, Startups, and Developer communities. • Work closely with AWS service teams, Service Specialist, PR, and other marketing managers to ensure the AWS message is reaching a broad audience via events, seminars, webinars, and other GTM activities. • Build an effective evangelism content plan to drive awareness, adoption, and usage of the AWS platform. • Co-work with key persons in the appropriate partners to make new IT trend. • Travel, as necessary to execute marketing initiatives.