安克创新AI Engineer Intern
任职要求
Qualifications & Skills - Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field. - Strong foundation in Python programming and basic knowledge of C/C++. - Interest and understanding of computer vision, AI development, and real-time image/video processing. - Familiarity with deep learning frameworks such as PyTorch and TensorFlow is a plus. - Basic …
工作职责
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.
We are looking for a Generative AI Intern Engineer to join the NVIDIA Developer Technology group (Devtech) and work with a team of experienced engineers on innovative uses of AI for games and content creation. The Devtech team works with NVIDIA researchers and leading game developers to bring cutting edge AI research from across NVIDIA and the industry to gamers and 3D professionals in high performance packages such as real-time inferenced graphics, physics and animations. What you’ll be doing: • Research and implement innovative generative AI algorithms for game engines and authoring tools, including real-time neural graphics, physics based animation and diffusion models. • Develop neural graphics, animation and physics models and maintain open-source projects for both game-making and user runtimes. Integrate them into mainstream game engines and DCC tools. • Use various optimization techniques, such as tensor fusion and quantization, to fit the AI models onto user devices and maximize the performance of inference for real-time gaming. • Collaborate with game developers on optimizations and improvements for specific GenAI applications. • Interact closely with the architecture and driver teams at NVIDIA in ensuring the best possible experience on current generation hardware, and on determining trends and features for next generation architectures.
AI 渲染方向实习生 AI Rendering Engineer Intern（Animation & Interactive Engine） 一、岗位介绍 我们正在构建新一代 AI 驱动的动画编辑器与互动渲染系统，通过大模型提升动画生成与互动代码生成的效率与准确率。 本岗位聚焦于： - AI 动画结构生成 - AI 互动逻辑代码生成 - Agent 系统设计 - 模型评估与微调 - 渲染系统与大模型协同优化 这是一个融合 大模型 + 渲染引擎 + Agent 架构 + 训练评估体系 的技术岗位。 二、岗位职责 1. 构建 AI 渲染生成系统 - 基于大模型生成动画结构（Timeline / Node Graph / Keyframe） - 生成互动逻辑代码（JavaScript / TypeScript） - 构建结构化生成约束机制（Schema / AST 约束） - 设计模型生成结果的稳定性增强策略 2. 设计与实现 Agent 工具体系 - 设计多工具协作的 Agent 架构 - 实现动画结构查询与修改工具 - 实现代码执行与运行时验证工具 - 构建错误检测与自动修复闭环 3. 建立 AI 生成准确率评估体系 - 构建自动化 Benchmark 数据集 - 设计评估指标（Compile Rate / Runtime Rate / Logical Accuracy） - 搭建自动测试 Pipeline - 分析模型错误分布并持续优化 4. 数据构建与模型优化 - 构建动画与互动代码训练数据 - 数据清洗与标注规范设计 - 参与模型微调（SFT / LoRA） - 优化模型在结构化生成任务中的表现
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.
• Work and develop state of the art techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures • You will provide the best AI solutions using GPUs working directly with key customers • Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models