We are now looking for a Senior AI Training Performance Engineer! NVIDIA is seeking senior engineers who are obsessed with performance analysis and optimization to help us squeeze every last clock cycle out of AI training, one of
Change the world. Love your job. In your first year with TI, you will participate in the Career Accelerator Program (CAP), which provides professional and technical training and resources to accelerate your ramp into TI and set
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NVIDIA is seeking Software Performance Architects to optimize GPU kernel performance for state-of-the-art data-center platforms. We build automated, data-driven workflows to detect, explain, and prevent performance regressions across key deep learning workloads, partnering closely with kernel
NVIDIA is looking for a talented Performance Research and Analysis Engineer to join our Performance group. The ideal candidate will profile and analyze AI workloads on large GPUs and CPUs scale clusters for distributed Deep Learning
Job Description SummaryActivities contributing to the design and development of products and their interaction with the human body. Responsible for departmental operations planning/execution or is focused on execution of professional activities within a technical discipline. Functions
校招-座舱大模型后训练/Agentic 算法工程师 北京、上海 校招 正式 数字技术 - 算法 硕士及以上 2027届校园招聘-正式批 职位 ID：A178013 职位描述 1. 面向智能座舱与车载交互场景，探索大语言模型与 Agent 在真实产品中的应用，负责车载对话系统、任务型助手、多轮交互Agent等方向的研究、训练优化、效果评估与产品迭代。2. 跟踪并复现 LLM 后训练与 Agentic Training 前沿技术，包括 On-policy Distillation、Agentic RL、RLHF / RLVR 等，推动其在车载智能体、复杂任务执行、多工具调用和多轮推理决策中的落地。3. 参与构建 Agent 能力增强所需的训练与交互环境，包括 Tool 系统、User Simulator、World Model、Reward Function、Agent Harness、任务编排与自动化评测框架等。4.
大模型领域后训练算法工程师 北京、上海 社招 全职 数字技术 本科及以上 工作年限不限 职位描述 1. 设计并实现面向车载人机智能交互系统的后训练算法流程，优化多轮对话决策、任务规划等agent能力。2. 负责调研、复现LLM agentic RL等post-training相关的前沿研究，探索将新技术应用于实际产品。3. 协助实车数据问题挖掘、分析及解决方案制定等。4. 协助设计并实现增强基模agent相关能力的交互环境、user simulator、world model、reward function等关键模块。 职位要求 1. 本科及以上学历，计算机、自动化、信号处理等相关专业，数理基础扎实，乐于在强化学习方向深入探索。2. 熟练掌握Python/JAVA/TypeScript/JsonScript等编程语言（一门及以上）。3. 熟悉LLM agent相关概念，深入理解ReAct、function call、TIR、reflection等相关范式。4. 熟练掌握LLM RL主流算法原理，如PPO、GRPO、DAPO等，对agentic RL范式有研究兴趣，有实际项目经验为佳。5. 熟悉相关蒸馏算法，包括off-policy distillation及on-policy distillation等范式。6. 熟悉常见后训练、强化学习框架，包括但不限于Verl、Slime、ms-swift、OpenRLHF、TRL等。对大规模分布式机器学习框架有一定了解，对training、inference相关infra工作感兴趣。7. 熟悉语音对话系统，或有高水平论文发表者优先。 投递...
大语言模型后训练/Agentic算法工程师 上海、北京 社招 全职 数字技术 本科及以上 工作年限不限 职位描述 岗位亮点参与构建面向智能座舱场景的下一代大模型 Agent，推动 LLM 后训练、Agentic RL、多工具调用、多轮推理决策等前沿技术在真实车载产品中落地，持续提升模型在真实用户、真实车辆、真实场景中的可靠性与体验。面向智能座舱与车载交互场景，探索大语言模型与 Agent 在真实产品中的应用，负责车载对话系统、任务型助手、多轮交互Agent等方向的研究、训练优化、效果评估与产品迭代。跟踪并复现 LLM 后训练与 Agentic Training 前沿技术，包括 On-policy Distillation、Agentic RL、RLHF / RLVR 等，推动其在车载智能体、复杂任务执行、多工具调用和多轮推理决策中的落地。参与构建 Agent 能力增强所需的训练与交互环境，包括 Tool 系统、User Simulator、World Model、Reward Function、Agent Harness、任务编排与自动化评测框架等。基于实车交互数据和线上反馈，进行问题挖掘、错误归因与方案优化，建设数据生产、模型训练、离线评测、在线分析和失败案例回流的闭环体系，推动大模型能力从“可用”走向“好用、可靠、可持续进化”。 职位要求 研究生及以上学历，计算机、人工智能、自动化、信号处理、数学等相关专业，具备扎实的机器学习与 NLP 基础。具备
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