Job description Production Operator / Food Production Assistant 工厂员工 (AIR CON, WALKING DISTANCE FROM PAYA LEBAR MRT) Job Description & Requirements RESPONSIBILITIES • Pack fruits and assist with fruit juice production • Check the quality of all food items to ensure they meet food safety standards. • Maintain cleanliness of the workplace. • Able to work in a clean and cool food production environment. • Assist with other ad hoc duties as required. QUALIFICATIONS • No experience needed (training provided). • Seniors are welcome to apply. • Must be comfortable standing while working. WORKING HOURS • Monday to Friday: 9:00 AM 6:00 PM • Saturday: 8:00 AM 12:00 PM (Half Day) • Sunday: Off • 5.5-day work week 职位描述 工作职责 • 负责水果及果汁产品的包装工作 • 检查食品质量 并进行品质控制 确保符合食品安全标准 • 保持工作场所整洁 卫生 • 能够适应食品生产环境 环境干净 凉爽 • 根据工作需要 协助完成其他临时安排的工作 任职要求 • 无需相关工作经验 公司提供培训 • 欢迎乐龄人士申请 • 能够接受长时间站立工作 工作时间 • 星期一至星期五 上午9:00至下午6:00 • 星期六 上午8:00至中午12:00 半天 • 星期日 休息 • 工作制度 每周工作5天半 5.5天工作制
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Senior Design Quality Engineer in India
1,053 active opportunities · Updated October 2026
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Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. Location : Bengaluru (On-site) + multi-city coordination Instawork Robotics Lab (IRL) Robots are getting smarter, but they still can’t reliably do the everyday physical tasks people do — chopping vegetables, stocking shelves, assembling parts. The bottleneck is data. UC Berkeley’s Prof. Ken Goldberg calls it the “100,000-year data gap”: the chasm between the massive text datasets used to train language models and the tiny amount of real-world, physical-dexterity data available to train robots. The entire robotics industry collected only ~100,000 hours of training data in 2024 and ~1 million in 2025 — and even the ~20 million hours projected for 2026 is still less than 0.04% of what is ultimately needed. IRL exists to close that gap. Using Instacore — a wearable multi-camera and sensor system (head, chest, and wrist cameras plus IMUs and a compute pack) — our field teams capture synchronized, high-diversity egocentric data of real people doing real tasks across real commercial environments: kitchens, warehouses, hotels, retail, and light manufacturing. That data is quality-checked, anonymized, and delivered to the world’s leading robotics companies and foundation-model labs to teach robots how to operate in the messy physical world. In India, we run the on-ground engine of this mission — a growing fleet of Instacore rigs, Field Officers and Data Collectors, regional hubs, and the operations and finance backbone that keeps it
Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. Instawork Robotics Lab (IRL) Robots are getting smarter, but they still can’t reliably do the everyday physical tasks people do — chopping vegetables, stocking shelves, assembling parts. The bottleneck is data. UC Berkeley’s Prof. Ken Goldberg calls it the “100,000-year data gap”: the chasm between the massive text datasets used to train language models and the tiny amount of real-world, physical-dexterity data available to train robots. The entire robotics industry collected only ~100,000 hours of training data in 2024 and ~1 million in 2025 — and even the ~20 million hours projected for 2026 is still less than 0.04% of what is ultimately needed. IRL exists to close that gap. Using Instacore — a wearable multi-camera and sensor system (head, chest, and wrist cameras plus IMUs and a compute pack) — our field teams capture synchronized, high-diversity egocentric data of real people doing real tasks across real commercial environments: kitchens, warehouses, hotels, retail, and light manufacturing. That data is quality-checked, anonymized, and delivered to the world’s leading robotics companies and foundation-model labs to teach robots how to operate in the messy physical world. In India, we run the on-ground engine of this mission — a growing fleet of Instacore rigs, Field Officers and Data Collectors, regional hubs, and the operations and finance backbone that keeps it all running at quality and scale. Role Overview The Finance Associat
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