苹果Intern - AI/ML Engineering Project for Product Regulatory Compliance and field database - Beijing

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.

An exciting internship opportunity to make an immediate contribution to AMD's next generation of technology innovations awaits you! We have a multifaceted, high-energy work environment filled with a diverse group of employees, and we provide outstanding opportunities for developing your career. During your internship, our programs provide the opportunity to collaborate with AMD leaders, receive one-on-one mentorship, attend amazing networking events, and much more. Being part of AMD means receiving hands-on experience that will give you a competitive edge. Together We Advance your career! JOB DETAILS: Location: Shanghai, China Onsite/Hybrid: This role require the student to work at least 3 days/week, either in a hybrid (minimum 3 Days in Office) or onsite work structure throughout the duration of the co-op/intern term. Duration: Jan - June 2026 WHAT YOU WILL BE DOING: We are seeking a highly motivated Machine Learning (ML)/Artificial Intelligence (AI) intern/co-op to join our team and contribute to the development of next-generation product differentiation features alongside expert ML/AI engineers. In this role, you will: Gain hands-on experience with cutting-edge technologies in ML, AI, and High-Performance Computing. Learn to analyze and optimize GPU Kernel to maximize performance for specific AI operations. Contribute to projects such as: Researching, developing, and deploying machine learning and computer vision solutions for AMD's current and future products. Work closely with internal teams to analyze and improve training and inference performance on AMD GPUs. Design and optimize deep learning models specifically for AMD GPU performance. Assisting AI software teams with roadmap planning, collateral development, and customer engagements. Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream. Apply sound engineering principles to ensure robust, maintainable solutions.

We are now looking for a Performance Engineer Intern to support our growing investments in perf testing of various company datacenter products and applications. Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world, all while striving to deliver the highest possible performance of our products.You will be part of global Performance Lab team, improving our capacity to expertly and accurately benchmark state-of-the-art datacenter applications and products. We also work to develop infrastructures and solutions that enhance the team’s ability to gather data through automation and designing efficient processes for testing a wide variety of applications and hardware. The data that we collect drives marketing/sales collaterals as well as engineering studies for future products. You will have the opportunity to work with multi-functional teams and in a dynamic environment where multiple projects will be active at once and priorities may shift frequently. What you’ll be doing: • Benchmark, profile, and analyze the performance of AI workloads specifically tailored for large-scale LLM training and inference, as well as High-Performance Computing (HPC) on NVIDIA supercomputers and distributed systems. • Aggregate and produce written reports with the testing data for internal sales, marketing, SW, and HW teams. • Develop Python scripts to automate the testing of various applications. • Collaborate with internal teams to debug and improve performance issues. • Assist with the development of tools and processes that improve our ability to perform automated testing. • Setup and configure systems with appropriate hardware and software to run benchmarks.

• This role will involve in Software and Hardware R&D from initial phase, working on different wireless technologies(including 5G, LTE, NFC, GNSS technology, WiFi/Bluetooth, UWB) from design/prototype phase till finalization and post production/launch to end users. • You will work with our excellent Apple Engineering team on innovative project, in which you will be deeply involved into Product design, feature investigation, evaluation them in real world. • This includes to study and qualify relevant features at system level, from functional and performance perspective. Run focused experiments to understand and identify root cause of any issues and raise proposal of innovative ideas to influence the design from user experience point of view. • Assist to build up comprehensive database with various data from live network and real user scenarios • Work closely with Experienced Field Design Engineers and multi-functional teams to deep dive the data • Develop models based on Large-Scale data to predict potential issues, to support decision-making processes across teams