英伟达Performance Engineer Intern, Deep Learning and HPC - 2025

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.

As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state-of-the-art research in ML to tackle complex data problems. The solutions you develop will significantly impact future Apple products and the broader ML development ecosystem. You will work with a multidisciplinary team to actively participate in the data-model co-design and co-development practice. Your responsibilities will extend to the design and development of a comprehensive data curation framework. You will also create robust model evaluation pipelines, integral to the continuous improvement and assessment of ML models. Additionally, your role will entail an in-depth analysis of collected data to underscore its influence on model performance. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues. Your work may span a variety of topics, including but not limited to: * Designing and implementing semi-supervised, self-supervised representation learning techniques for maximizing the power of both limited labeled data and large-scale unlabeled data. * Developing evaluation protocols centered on the end-to-end user experience, with a focus on anticipating potential failure modes, edge cases, and anomalies. * Employing data selection techniques such as novelty detection, active learning, and core-set selection for diverse data types like images, 3D models, natural language, and audio. * Uncovering patterns in data, setting performance targets, and leveraging modern statistical and ML-based methods to model data distributions. This will aid in reducing redundancy and addressing out-of-distribution samples.

We are now looking for a software engineer intern. The NVIDIA Developer Tools team is seeking a software engineer intern to join our effort to advance the state of graphics and compute performance analysis and tuning. You will help developers of groundbreaking products in Automotive, VR, Gaming, Deep Learning and High Performance Computing to analyze and improve the performance of their products. You will have the opportunity to learn the pipeline and driver stack of the world's most sophisticated GPUs, work with a group of talented engineers from all over the world, and apply your software development skills to improve our products. What you’ll be doing: • Develop algorithms to exercise various parts of the GPU pipeline to verify our performance metrics. • Deeply dive into NVIDIA GPU architecture and software stack, develop new feature for NVIDIA GPU performance profiling tools. • Write unit and integration tests to verify the functionality, performance, stability, resource usage of our products.

About Us Anker Innovations is a technology company dedicated to creating industry-leading smart devices for entertainment, travel, and smart homes. At the forefront of AI innovation, we develop reliable, high-quality AI applications to enhance the quality of care and provide exceptional user experiences. We are seeking driven individuals who are passionate about technology to help build cutting-edge, consumer-facing solutions. Job Summary We are seeking an AI Intern with a focus on JD-AI (Joint Deep AI) Engineering to join our dynamic team. In this role, you will assist in the design, development, and deployment of deep learning models for edge IoT devices. You will collaborate with AI engineers to optimize models and applications for real-time image and video processing on embedded systems. This internship provides a unique opportunity to gain hands-on experience with cutting-edge AI technologies in the rapidly evolving field of smart devices and IoT. Key Responsibilities - Assist in the development, testing, and optimization of AI models for tasks such as object detection, segmentation, tracking, and action recognition. - Contribute to the enhancement of model performance for improved customer satisfaction and operational efficiency. - Help implement AI model compression techniques to deploy models effectively on IoT embedded platforms. - Collaborate with an agile development team to meet project requirements and deadlines. - Write clean, maintainable, and scalable code with a focus on performance and extensibility. - Support the maintenance of organized technical documentation throughout the project lifecycle.