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Kan du forklare attention på en serviet, træne en transformer fra bunden, og bygge de evals, der afslører, om den faktisk virker? Og vil du bruge dine evner på noget, der virkelig betyder noget? Så har vi en mission,…
Build and scale Databricks' managed GPU training platform (AI Runtime), designing systems for large-scale AI model training, fault tolerance, and developer experience.
Senior systems engineer based in Munich building the control plane for bare-metal AI/GPU infrastructure: Kubernetes operators and CRDs, GPU cluster scheduling, and driver/fabric tuning for distributed LLM training. Core stack: Python, Linux internals, Kubernetes, NVIDIA GPU tooling, Terraform/Ansible.
Designs and deploys end-to-end AI infrastructure for enterprises, integrating NVIDIA GPU clusters, high-performance networking, parallel storage, and AI software stacks to support large-scale model training and inference.
Lead a 3-person ML team building LLM-powered dialogue systems for Social Discovery Group's social products — owning ML strategy tied to business metrics, running LLM post-training (SFT, LoRA, DPO), designing tool-using agent systems, and building evaluation layers, with ~10–20% hands-on Python work.
1、围绕行业AI应用快速落地,研发端到端智能体核心技术,方向包括但不限于:Agent RL强化学习方法、全模态数据解析与私域知识加工、自规划和自主进化的多智能体等技术,提升智能体在复杂业务流中的效果与适应性。 2、攻坚突破大模型产品在行业应用落地和交付过程中的技术难题,与业界先进技术进行持续对比,并保持优势。 3、具备良好的产品化思维,驱动产品迭代,与产品和工程团队紧密合作,将算法技术应用于实际产品,带来产品商业化增量和竞争力。…
职位概述: 作为平头哥数据中心产品线软件解决方案定制工程师,主要负责为终端客户提供高水平的技术支持与软件解决方案,确保客户在使用平头哥数据中心产品及相关技术时获得最佳体验。 与客户建立紧密关系,推动客户满意度,并协调跨部门合作以解决复杂的技术问题。 主要职责: 协助客户完成技术评估和项目导入,解决客户AI芯片落地过程中相关问题,并能指导客户进行系统性调优,确保产品在客户业务场景中顺利落地。…
团队介绍:字节跳动基础设施网络团队,负责集团全球网络基础设施设计、研发及运营工作,包括全球骨干网、数据中心网络、AI高速网络、云网络、容器网络、四七层应用网络等,基于先进的交换芯片和光互连技术,我们通过自研交换机、光芯片打造高性能的数据中心网络;基于自研RDMA协议、拥塞算法、集合通信库的创新,我们打造了超大规模的AI高速网络;基于全自研的SDN、NFV、端到端的QUIC协议、拥塞算法以及软硬结合HPA,我们设计了拥抱时代的云计算网络…
Founding Solutions Architect at Prime Intellect who owns technical wins in AI infrastructure sales: running deep discovery on customers' training and inference workloads, designing architectures on Prime's GPU platform, and executing benchmarks and POCs that become defensible technical business cases. Core stack: GPUs/CUDA, distributed training and inference systems.
This position is for building, deploying and evaluating Client's Arabic AI tutor for mathematics and computer science: preparing Arabic training data, fine-tuning, aligning and evaluating LLMs on Shaheen III and…
1.长期记忆机制研发:负责大模型长期记忆全链路算法设计,实现记忆抽取、存储、检索、更新、遗忘,解决跨会话记忆一致性、冲突与时效性问题; 2.个性化用户建模:基于用户交互、行为数据构建用户模型,挖掘用户偏好、表达习惯,驱动模型动态适配,提升个性化交互体验; 3.记忆方向模型后训练:使用 SFT/RLHF/ 奖励建模等技术,把记忆调用、准确性、个性化目标转化为训练信号;构建高质量训练数据,搭建用户反馈驱动的模型迭代闭环;…
Who We Are You've ordered dinner through Just Eat Takeaway. You've bought and sold on OLX. You've paid with PayU. Chances are, you've already used a Prosus company today. We are Prosus, a global…
Senior ML Systems Engineer builds and maintains distributed AI training infrastructure for large-scale model training and reinforcement learning experiments using PyTorch, Megatron-LM, and DeepSpeed in Palo Alto.
负责多种AI 业务场景的性能瓶颈分析及需求量化分析,覆盖仿真工具设计与研发、模型性能预测、硬件瓶颈分析、客户业务场景技术栈分析、重点客户方案支持及产品特性方案设计,为灵骏集群架构设计与产品演进提供可量化的数据支撑。 核心职责 1. 参与开源或内部仿真平台的构建,支持特定模型在不同机型上的训练/推理场景瓶颈分析和性能对比评估 2. 为机型选型和网络规划提供定量的分析及仿真数据支撑 3.…
训练方向: 负责分布式训练框架的设计与优化,支撑医学大模型(LLM及多模态)的预训练、SFT微调、Post-Training(RLHF/GRPO/PPO等强化学习对齐)全流程训练任务。 构建高效稳定的训练数据Pipeline,包括数据预处理、数据加载与调度、Checkpoint管理(异步快照、分布式Checkpoint、断点续训)等基础设施。…
Machine Learning Engineer on InMobi's Ad Sciences team builds and optimizes ad intelligence models and the infrastructure behind them — training pipelines, LLM post-training infra (DeepSpeed, OpenRLHF), and low-latency inference — using Python, PyTorch, Spark, Kubernetes, and GPU/TPU acceleration at massive ad-serving scale.
Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager Job Description & Summary At PwC, our people in data and analytics focus on leveraging data to…
Обязанности: По данной вакансии просим звонить по номеру: 8 (800) 333-30-73. Обязанности: Проектировать и обучать большие языковые и мультимодальные модели (от 7B параметров): подготовка корпусов, токенизация,…
渴望为世界带来新意的人,早已对描绘未来的“热词”不陌生——人工智能、机器学习、数据科学等等。腾讯始终在业界前沿不断探索,积极布局,并为优秀的你提供无限广阔的舞台。我们坚信科技的不断革新,最终能带来美好的、撼动人心的改变。 1.负责大模型推理引擎架构设计、研发与迭代,深度适配主流GPU及异构AI芯片,优化推理性能与算力成本,搭建生产级PD分离推理调度系统,保障推理服务高并发、低延迟、高稳定;…
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