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Machine Learning Algorithm Engineer -- Manufacturing Data

AmpaceUnited, WV🇺🇸United StatesPosted Sep 30, 2026

Why This Role Stands Out

Leverage your machine learning expertise to drive innovation in battery manufacturing at a leading global company, with opportunities for significant impact and career growth. You'll thrive in this hybrid role if you possess a PhD, strong Python/MATLAB skills, and a passion for applying algorithms to real-world production challenges. Embrace the chance to contribute to cutting-edge technology and enhance manufacturing processes.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United, WV, United States
Posted
8 hours ago

Job Description

Job DescriptionAmpace (新能安) is a global battery-technology company specializing in lithium-ion cells and systems for energy storage, data centers, and critical power. Our R&D pairs advanced cell chemistry with semi-solid-state technology to deliver safe, high-performance batteries at scale. This position is based at our R&D center in Xiamen, China.\n\nResponsibilities:\n1. Clean, model, and analyze cell manufacturing-process data end to end.\n2. Develop machine-learning algorithms that reveal the drivers of quality and process performance.\n3.

Work with process and manufacturing teams to embed models into day-to-day production.\n\nRequirements:\n1. PhD in Computer Science or a closely related field.\n2. Strong programming in Python and MATLAB.\n3. Hands-on experience developing common machine-learning algorithms.\n4.

Willingness to learn cell design, manufacturing, and testing; strong communication and ownership.\n\n新能安(Ampace)是一家全球领先的电池科技企业,专注于锂离子电芯及电池系统的研发与制造,产品广泛应用于储能、数据中心及关键电源等领域。公司结合先进的电芯化学体系与半固态电池技术,致力于打造兼具高安全性、高性能和规模化生产能力的电池产品。\n本岗位工作地点位于中国厦门研发中心。\n\n岗位职责\n\n 负责电芯制造全过程的数据清洗、建模与分析,挖掘生产数据价值。\n 开发机器学习算法,识别影响产品质量和制造工艺性能的关键因素,为工艺优化提供数据支持。\n 与工艺开发及生产制造团队紧密协作,推动算法模型在生产现场落地应用,持续提升生产效率和产品质量。\n\n\n任职要求\n\n 计算机科学或相关专业博士学历。\n 熟练掌握 Python、MATLAB 等编程语言。\n 具备机器学习算法开发经验,熟悉常见机器学习算法及其应用。\n 愿意深入学习电芯设计、制造工艺及测试相关知识,具备良好的沟通协作能力和较强的责任心。\n\n\n

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