英伟达Machine Learning Intern, Humanoid Robotics - 2026
任职要求
• Currently pursuing a PhD or Master’s degree in Robotics, Computer Science, or a related field. • Strong academic or project track record demonstrating execution bandwidth in applied research and engineering on robotics platforms. • Hands-on experience with deep learning frameworks such as PyTorch, JAX, or TensorFlow, and physics simulation tools like Isaac Sim/Lab or MuJoCo. • Strong familiarity with foundation models for robotics and 3D perception. • Experience with sim-to-real and real-to-sim transfer in robotics. • Deep knowledge of robot learning, …
工作职责
• Collaborate with researchers and engineers on focused projects in humanoid robotics loco-manipulation and mobile manipulation areas. • Support the development and advancement of GR00T and Cosmos foundation models. • Help develop reference workflows with Isaac Lab and Newton for humanoid and mobile manipulation dexterous tasks. • Advanced technologies for robot learning and synthetic data generation using human videos. • Design, implement, and test novel algorithms for humanoid robot locomotion and manipulation in both simulated and real-world environments. • Drive a scoped internship project from model/algorithm design and sim-to-real transfer through to on-robot validation, with the potential for open-source contributions or publications. • Collaborate cross-functionally with teammates and partners to share findings and advance shared goals.
1、负责搭建快手NLP技术体系，包括但不限于文本分类、知识图谱、翻译、对话等； 2、与业务部门进行沟通与协作，交付满足产品需求的核心算法模型与能力。
1、负责AI小快智能助理机器人的研究和开发； 2、优化基础模型，并采用RAG、Agent等大模型衍生框架，来提升相关业务指标； 3、持续跟进并深入调研大模型前沿技术、开源方案，跟踪业内大模型领域的最新进展并推进相关研究，探寻将最新技术应用到AI小快的可能性。
1、模型研发与优化： 负责从0到1构建和迭代机器学习/深度学习模型（如：异常检测、图神经网络、自然语言处理、时间序列分析等），应用于恶意代码分类、网络入侵检测、用户行为分析、钓鱼网站识别等具体场景； 2、威胁狩猎与研究： 利用机器学习模型发现未知威胁和攻击模式，参与安全事件的分析与响应，为安全策略的制定提供数据驱动的洞察； 3、大模型智能体的落地：探索大模型结合信息安全领域的应用，如攻击告警自动化处理等； 4、数据探索与特征工程： 深入分析海量安全数据（如日志、流量、恶意样本、威胁情报等），进行数据清洗、特征提取和特征工程，为模型训练提供高质量的数据基础； 5、前沿技术探索： 跟踪学术界和工业界在AI安全领域的最新进展，评估并将有潜力的新技术（如：联邦学习、对抗机器学习、自监督学习等）应用于实际业务，解决诸如样本稀缺、对抗性攻击等挑战。
• Lead the product planning and execution of the platform’s recommendation system to improve the accuracy and effectiveness of personalized recommendations. • Analyze user behavior and purchase data to identify needs and preferences, and optimize recommendation algorithms accordingly. • Collaborate with data scientists and engineering teams to drive the development and enhancement of recommendation algorithms. • Develop and manage the product roadmap, ensuring timely delivery of projects that meet quality standards. • Monitor key performance indicators of the recommendation system, provide optimization suggestions, and implement improvement plans. • Work with marketing and user experience teams to ensure that recommendation product features align with the overall user experience.