苹果AIML- Infrastructure Systems Engineer (Machine Learning), Machine Learning Platform Technologies

The Infrastructure Systems Engineer 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 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 - Develop and implement the above design, bringing it to an internal product, with observability to support efficient system management - Design and/or enhance 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 - Support Dev and Eng efforts through provisioning operational solutions, co-design ML application architecture and drive the coordination among local and global, internal and cross-functional groups to achieve the result of success - Create performance profile for platforms and services, defining service level objectives (SLO) and driving the measurement, monitoring and evaluation over these objectives - Lead constant evaluation on system performance and reliability, discover potential faults, drive RCA and fixes

• 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

- As an AIML Specialist Solutions Architect (SA) in AI Infrastructure, you will serve as the Subject Matter Expert (SME) for providing optimal solutions in model training and inference workloads that leverage Amazon Web Services accelerator computing services. As part of the Specialist Solutions Architecture team, you will work closely with other Specialist SAs to enable large-scale customer model workloads and drive the adoption of AWS EC2, EKS, ECS, SageMaker and other computing platform for GenAI practice. - You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage AI Infrastructure on Amazon Web Services. You will also create field enablement materials for the broader SA population, to help them understand how to integrate Amazon Web Services GenAI solutions into customer architectures. - You must have deep technical experience working with technologies related to Large Language Model (LLM), Stable Diffusion and many other SOTA model architectures, from model designing, fine-tuning, distributed training to inference acceleration. A strong developing machine learning background is preferred, in addition to experience building application and architecture design. You will be familiar with the ecosystem of Nvidia and related technical options, and will leverage this knowledge to help Amazon Web Services customers in their selection process. - Candidates must have great communication skills and be very technical and hands-on, with the ability to impress Amazon Web Services customers at any level, from ML engineers to executives. Previous experience with Amazon Web Services is desired but not required, provided you have experience building large scale solutions. You will get the opportunity to work directly with senior engineers at customers, partners and Amazon Web Services service teams, influencing their roadmaps and driving innovations.

• Collaborate closely with our AI/ML researchers to make their ML models more efficient leading to significant productivity improvements and cost savings • Build tools, frameworks, and apply ML techniques to detect & analyze efficiency bottlenecks and deliver productivity improvements for our researchers • Work with researchers working on a variety of innovative ML workloads across Robotics, Autonomous vehicles, LLM’s, Videos and more • Collaborate across the engineering organizations to deliver efficiency in our usage of hardware, software, and infrastructure  • Proactively monitor fleet wide utilization patterns, analyze existing inefficiency patterns, or discover new patterns, and deliver scalable solutions to solve them • Keep up to date with the most recent developments in AI/ML technologies, frameworks, and successful strategies, and advocate for their integration within the organization.