Mechanical Systems Engineer-shenzhen To strengthen our e-Bike Mechanical System Engineering team in Shenzen, China, we are seeking for a Mechanical Systems Engineer to commence immediately or by agreement. In this role, you will be developing solutions for state-of-the-art
Our Journey The ShopBack Group is Asia-Pacific’s leading shopping, rewards, and payments platform, serving over 20 million active members across 13 markets. In 2025, the Group continued its global growth with its expansion into North America.
About the job Delart is home to a team of world-class engineers and project leaders dedicated to developing the next generation of advanced networking technologies, consumer devices, and innovative technology solutions. Trusted by some of the world’s
Company Description At Digital Shelf by NIQ, we’re passionate about technological innovation and excellence in cybersecurity. Our cutting-edge solutions enable us to scrape data for 12 billion products and manage over 20 billion data points. In
Job Description • Reverse Engineering & Decompilation: Analyze web and mobile applications (APK/IPA) to uncover hidden mechanisms. Disassemble code to understand its inner workings, with a focus on cryptographic functions that secure our systems. • Overcoming
About Overview.ai Overview.ai is bringing the cutting edge of AI computer vision to manufacturing—solving inspection problems that were previously not solvable with traditional machine vision. We’re a full-stack company: we deploy GPU-powered cameras on production lines, run
Company Description WD is building the infrastructure behind the AI-driven data economy. As AI scales, so does data. Every interaction, every model, every system generates data that must be stored, managed, and made accessible over time.
About Us Dyson is a global technology company that sets out to solve the problems others ignore. We create machines that are different, better and more useful through inventive engineering, relentless testing and a refusal to accept
Company Description WD is building the infrastructure behind the AI-driven data economy. As AI scales, so does data. Every interaction, every model, every system generates data that must be stored, managed, and made accessible over time.
NVIDIA is seeking a highly skilled and motivated CPU Optimization Engineer to join our Compute Developer Technology (Devtech) team. In this role, you’ll research, design, and implement performance optimization strategies across a broad range of workloads—including AI
About Wati Started as a WhatsApp team inbox in 2020, Wati has evolved into an AI-powered customer engagement platform that goes beyond a single channel. Designed for businesses that sell, support, and grow through conversations, Wati
We are seeking an experienced Backend Engineer to join our growing Platform team. As a Backend Engineer, you will be a key contributor to the development, implementation, and maintenance of our core B2B logistics products, working closely with
Job Description As a Sr. Staff Marketing Manager for Physical AI & Humanoid Robotic Solutions, you will develop and execute the marketing and positioning strategy for Renesass integrated solutions across the robotics segment in the South
aNVIDIA’s Solutions Architect team is looking for a software-focused Solutions Architect to drive adoption of next-generation AI infrastructure across NVIDIA CPU platforms and LPU-based inference systems. This role will focus on NVIDIA CPUs, including Grace, Vera,
Wati is the worlds leading WhatsApp-first conversational growth platform, empowering businesses to build deeper customer relationships and accelerate revenue growth. Trusted and loved by over 14,000 customers across 100+ countries, Wati has established itself as the
我们正在寻找一位 全栈工程师，参与核心 AI Agent 产品从架构设计、能力建设到生产落地的完整过程。你将参与 Web 产品、API 服务、Agent 编排系统、后台任务系统、数据层和部署流程等多个环节，和团队一起构建面向真实生产环境的 AI Agent 产品。 你将深度参与 AI Agent 系统的工程化建设，包括 Agent Loop、工具调用、任务编排、多步骤执行、上下文管理、模型路由、异步任务处理、结果持久化、错误恢复、日志追踪与系统可观测性等关键模块。这个岗位不是简单调用大模型 API，而是需要将 LLM 能力、业务流程、前后端系统和用户体验结合起来，构建可稳定运行、可持续扩展的生产级 Agent 产品。 在这个角色中，你需要理解 Agent 如何接收用户目标、拆解任务、选择工具、执行动作、处理中间状态、根据反馈继续推理，并最终产出可靠结果。你也需要关注 Agent 执行过程中的实际工程问题，例如任务超时、工具失败、重试策略、状态一致性、成本控制、并发执行、队列调度、数据追踪以及生成结果的可复现性。 你会和产品、设计、前端、后端和基础设施团队紧密协作，把 AI 能力落到真实的产品体验中。我们希望你既能理解前端产品形态和用户交互，也能深入后端服务、数据模型、任务队列和 Agent 编排系统，帮助团队搭建长期可维护、可扩展、可观测的 AI Agent 工程体系。