Software Engineer at Tomra

Huli District, Fujian, China -

Full Time

Start Date

Immediate

Expiry Date

23 Apr, 26

Salary

0.0

Posted On

23 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Machine Learning, TensorFlow, PyTorch, Transformer Architectures, Attention Mechanisms, Positional Encoding, Cross-Modal Fusion, VLA, MLLM, LangChain, LangGrap, LlamaIndex, RAG, MCP, ROS, ROS2

Industry

Automation Machinery Manufacturing

Description

公司介绍 About TOMRA TOMRA was founded on an innovation in 1972 that began with the design, manufacturing and sale of reverse vending machines (RVMs) for automated collection of used beverage containers. Today TOMRA provides technology-led solutions that enable the circular economy with advanced collection and sorting systems that optimize resource recovery and minimize waste in the food, recycling and mining industries and is committed to building a more sustainable future. TOMRA has ~100,000 installations in over 80 markets worldwide and had total revenues of ~1.1 billion NOK in 2021. The Group employs ~4,600 globally and is publicly listed on the Oslo Stock Exchange (OSE: TOM). TOMRA group established a wholly-owned subsidiary in Xiamen, China in 2010, including 2 business divisions of collection and sorting. As the headquarters of Greater China, TOMRA carries out the export of core modules and spare parts of collection equipment import and sales of complete sets of sorting equipment. In early 2015, the sorting division established a R&D center in Xiamen to carry out independent R&D, production and sales in the market segments of sorting equipment, focusing on the Chinese market and promoting to global customers. 关于陶朗集团陶朗集团成立于1972年，创立之初，陶朗主要设计、制造和销售用于收集废弃饮料瓶的自动退瓶机。如今，陶朗提供技术领先的行业解决方案，包括先进的废弃物收集系统，以及用于资源回收、食品、矿产等领域的领先分选技术，致力于创造一个更可持续的未来。陶朗集团在全球80多个国家和地区拥有约10万台设备安装量，2021年总收入约为11亿欧元。集团在全球拥有约4600名员工，并在奥斯陆证券交易所（OSE:TOM）上市。陶朗集团于2010年在中国厦门成立全资子公司，包含收集和分选两大事业部，并作为大中华区总部，开展收集设备核心模块和零配件的出口、分选设备的整机进口和销售。 2015年初, 分选事业部进一步在厦门成立了研发中心, 针对分选设备的细分市场领域进行独立自主的研发、生产和销售，以中国市场为重心并推向全球客户。职位描述 Position Overview：职位概况: Contribute to transitioning LLM or VLA models from research prototypes to our digital system and edge devices, enabling low-latency, high-reliability visual perception to monitor machines in field and action decision-making. 参与将前沿多模态大模型或VLA模型从实验室推向我们的远程数字中心系统以及设备边缘设备，实现低延迟、高可靠的视觉理解以监测及控制现场设备。 Fine-tune, deploy, and optimize Multimodal Large Language Model (MLLM) or Vision-Language-Action (VLA) model. 多模态大模型或VLA模型的微调、部署和优化。 Main Responsibilities: 工作职责: Deploy LLM on the digital system to monitor the real-time operational status of on-site equipment and provide instant feedback. 在数字中心系统上部署大模型以实时监控现场设备运行状态及实时反馈。 Responsible for the development, deployment, and optimization of Vision-Language-Action (VLA) or Multimodal Large Language Model (MLLM) applications. 负责视觉-语言-行动模型(VLA)和多模态大模型(MLLM)应用的开发、部署与优化工作。 Perform domain-specific fine-tuning of VLA/MLLM models to adapt them to targeted robotic tasks and operational scenarios, enhancing task-specific accuracy and robustness. 针对特定机器人任务和场景，对 VLA/MLLM 模型进行微调（Fine-tuning），提升模型在特定任务上的性能。 Document and maintain software architecture, API, and technical guides for development and support teams. 为开发和技术支持撰写并维护软件的相关文档。职位要求 Bachelor's degree or higher, with basic English listening, speaking, reading, and writing skills. 本科及以上学历，具备基础的英语听说读写能力。 Proficient in Python Expertise in machine learning frameworks such as TensorFlow/PyTorch. 熟练掌握 Python，精通Tensorflow/PyTorch等机器学习框架。 In-depth knowledge of Transformer architectures (including attention mechanisms, positional encoding, and cross-modal fusion techniques). 深入了解Transformer架构（包括注意机制、位置编码和跨模态融合技术）。 Familiarity with VLA and MLLM architectures, with hands-on experience in training and fine-tuning multimodal large models. 熟悉 VLA\MLLM模型架构，具备多模态大模型训练与调优经验。 Familiarity with frameworks such as LangChain, LangGrap, and LlamaIndex; familiarity with large model-related technologies like RAG and MCP is preferred. 了解LangChain、LangGrap、LlamaIndex等框架，熟悉RAG、MCP等大模型相关技术优先。 Familiar with ROS/ROS2 robotics frameworks; preference will be given to candidates with hands-on experience deploying VLA models on real robotic platforms (e.g., NVIDIA Isaac GR00T) and successfully executing practical robotic tasks. 了解 ROS/ROS2 机器人操作系统，有在真实机器人平台（如NVIDIA Isaac GR00T）上部署 VLA 模型并完成实际任务的经验者优先。额外信息 1. Position available for start-up as soon as possible. 职位就绪，可即刻入职。 2. Probation period: 6 months. 试用期：6个月。

Responsibilities

The role involves deploying LLM on digital systems to monitor equipment and provide feedback, as well as developing and optimizing VLA and MLLM applications. Additionally, the engineer will fine-tune models for specific robotic tasks and maintain software documentation.