苹果Field Design Engineer Intern - Beijing

Bringing the State of the Art to Products  Collaborates with and bridges the gap between researchers (in community, Microsoft Research [MSR], or in their own organizations) and development teams. Brings new technology and approaches into production by applying long-term research efforts to solve immediate product needs.  With limited guidance from others, works to create product impact. Identifies approach, and applies, improves, or creates a research-backed solution (e.g., novel, data driven, scalable, extendable) to positively impact a Microsoft product or service. Solves components or aspects of a problem as assigned by a senior team member. May publish research to promote receiving new intellectual property for product impact.  Participates in collaborative relationships with relevant product and business groups inside or outside of Microsoft and provides expertise or technology to create business impact. Participates in technology transfer attempts, filing patents, authoring white papers, developing or maintaining tools/services for internal Microsoft use, or consulting for product or business groups. May publish research to promote receiving new intellectual property for business impact.  Capability Management and Networking  Maintains ties with external network of peers and identifies prospective talent, when asked. May contribute to publications on research findings. May participate in candidate interviews. Collaborates with the academic community to develop the recruiting pipeline and establish awareness of their work.  Reinforces a positive environment by applying best practices. May support mentorship by assisting with onboarding of research interns or other entry-level team members, if applicable.  Documentation  Performs documentation of work in progress, experimentation results, plans, etc. Documents scientific work to ensure process is captured. Participates in the creation of informal documentation and may share findings to promote innovation within group.  Ethics and Privacy  Understands and follows ethics and privacy policies when executing research processes and/or collecting data/information.  Leveraging Applied Research  Applies strategy by understanding the role in the team and applying the strategy provided by senior team members and incorporates state-of-the-art research. Asks probing questions to better understand strategy.  Researches and develops an understanding of tools, technologies, and methods being used in the community that can be utilized to improve product quality, performance, or efficiency. Contributes knowledge around several specialized tools/methods to support the application of business impact or serves as an expert in a deeply specialized area.  Gains deep knowledge in a service, platform, or domain and acquires knowledge of changes in industry trends and advances in applied technologies. Consults with engineers and product teams to apply advanced concepts to product needs. Learns product domain by reviewing products.  Machine Learning Functionality, Insights, and Technical Tools  Prepares data to be used for analysis by reviewing criteria that reflect quality and technical constraints. Reviews data and suggests data to be included and excluded. Describes actions taken to address data quality problems. Assists with the development of useable datasets for modeling purposes. Supports the scaling of feature ideation and data preparation. Helps take cleaned data and adapts for machine learning purposes, under the direction of a senior team member. Seeks guidance from senior team members when confronted with problems/challenges.  Uses machine learning algorithms that structures, analyzes, and uses data in product and platforms to train algorithms for scalable artificial intelligence solutions before deploying. Begins to develop new machine learning improvements independently while under the direction of a senior team member.  Collaborates to leverage data to identify pockets of opportunity to apply state-of-the-art algorithms to improve a solution to a business problem. Uses statistical analysis tools for evaluating Machine Learning models and validating assumptions about the data while also reviewing consistency against other sources. Begins to independently run basic descriptive, diagnostic, predictive, and prescriptive statistics. Assists with the communication of insights under the direction of senior team members.  Supports the application and use of intelligence created during the training of algorithms for deployment. Seeks information about large-scale computing frameworks, data analysis systems, and modeling environments to improve models. Helps create a model, apply the model to real products, and then verify effects through iterations. Helps with experiments by putting multiple models in production and evaluating their performance. Sets up monitoring and implementation to track production models, under the direction of a senior team member. Addresses models when that break, under the direction of others.  Leverages or designs and uses machine learning/data extraction, transformation, and loading (ETL) of pipelines (e.g., data collection, cleaning) based on data prepared. 

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 Onsite/Hybrid: This role requires the student to work full time (40 hours a week), either in a hybrid or onsite work structure throughout the duration of the co-op/intern term. Duration: January 1, 2026 - June 30, 2026 WHAT YOU WILL BE DOING: We are seeking highly motivated AI/ML Engineering Intern to join our AMD Research team. In this role: You will develop machine learning models to optimize GPU power/performance tradeoffs using real-world silicon data. We will train you to deploy models via MLOps pipelines for AMD’s internal tools. Your responsibility will include analyzing hardware telemetry data (power, thermal, clocks) to identify efficiency bottlenecks. You will collaborate with hardware engineers to validate models on next-gen AMD GPUs. Learning Outcomes: Master GPU-accelerated ML workflows. Gain hands-on experience with industrial-scale MLOps.

Change the world. Love your job. As a Digital IC Design Engineering intern, you'll architect new TI products and make our customers' visions a reality. You'll define, design, model, implement and document analog, digital, and RF integrated circuits (ICs). And, you'll have the opportunity to work in exciting areas like audio, imaging, high-speed, interface, clocking, medical, high volume linear, automotive, storage, power supply, battery management, linear power and many more. Some of your responsibilities will include, but will not be limited to: • Partnering with business teams and system engineering to develop mutually agreeable design specifications • Providing high-level analysis on chip architecture trade-offs to ensure spec compliance and superior performance at a competitive cost • Participating in design reviews and creating the necessary design and product documentation • Partnering on IC layouts to ensure a high-performance standard • Characterizing prototypes, developing test specifications and coordinating with test/product engineering to drive product releases • Driving behavioral models Put your talent to work with us as a Digital IC Design Engineer Intern! Texas Instruments will not sponsor job applicants for visas or work authorization for this position.

• Candidate will be responsible for: • - Collaborate with senior engineers to design and develop ML tools for data processing, analysis, and visualization. • - Integrate and validate machine learning models on Apple new product introduction (NPI) process and mass production. • - Develop and implement automated pipelines for model training and evaluation. • - Conduct experiments to evaluate the effectiveness of different models and algorithms. • - Participate in code reviews, testing, and documentation to ensure high-quality and maintainable code. • - Keep up-to-date with the latest advancements in machine learning and data science techniques.