职位&公司对比

职位详情

• 深圳
• 5-10年
• 本科

• 深度学习
• 图像算法
• 自然语言处理算法
• 推荐算法
• Python
• 算法工程化经验

Job description: WHERE YOUR EXPERTISE IS NEEDED Responsible for applied science initiatives in the fashion e-commerce domain, encompassing research strategy, roadmap planning, and project execution. Focused on user-centric needs, leveraging AI and large language model (LLM) technologies to establish a cutting-edge domain-specific knowledge platform, drive intelligent content creation, and develop smart assistant solutions that innovate user interaction experiences. Take end-to-end ownership for developing, deploying, and operating machine learning solutions on our centralized abuse protection platform for detecting and managing transactional risks Raise the analytical and technical bar within the applied science domain by improving processes and documentation Quick prototyping and spiking of machine learning models to assess their applicability for solving research, customer, and business problems Tackle challenges for developing algorithms and running them efficiently on resource constrainkanzhuned platforms Rigorous approach in solving, conducting, and documenting research projects Work in a cross functional team consisting of software applied scientists, engineers, product managers, and product analysts Contribute to our growing science community and encourage knowledge sharing in an agile work environment WHAT WE’RE LOOKING FOR： Solid hands-on experience as an applied scientist, developing and productionizing machine / deep learning models in cloud environments (preferably AWS) Proficient in large model frameworks such as Llama/Qwen and their applications, with solid experience in prompt engineering. Skilled in conducting supervised fine-tuning (SFT) and knowledge enhancement by integrating domain-specific data Good proficiency in Python and related machine / deep learning frameworks, such as Pytorch, Tensorflow, Keras, etc. Expertise in machine learning infrastructure and tooling, such as Databricks, Spark, Flink, relational databases, AWS SageMaker, S3, EC2, Step Functions, Git Experience with data storage, ingestion, and transformation, also including machine learning workflow orchestration Passion for developing clean, well maintainable, and testable code Motivation for continued personal development in discovering new technologies and software services Curiosity and来自BOSS直聘 eagerness to understand the business context where the team operates and the customer problem直聘s being solved Very good communication skills to translate (even complex) analytical / engineering decisions and outcomes to broader, non-technical audience 工作职责： 负责时尚电商的应用科学工作，包括研究战略、路线规划及项目。 围绕用户需求，使用AI及大模型技术，构建领先的领域知识平台，内容创作和智能助手，创新用户互动体验。 通过改进流程和文档，提高应用科学领域的分析和技术标准。 对机器学习模型进行快速原型制作和探索，评估其在解决研究、客户及业务问题方面的适用性。 应对在资源受限平台上开发算法并高效运行算法的挑战。 以严谨的方式解决、开展和记录研究项目。 在一个跨职能团队中工作，团队成员包括软件应用科学家、工程师、产品经理和产品分析师。 为我们不断壮大的科学社群做出贡献，并在敏捷的工作环境中鼓励知识共享。 岗位要求： 具备扎实的应用科学家实践经验，在云环境（优先考虑 AWS）中开发机器学习 / 深度学习模型并将其投入生产。 熟悉llama/Qwen等大模型框架以及应用， 具备良好的Prompt指令开发经验，能够结合领域数据做SFT和知识增强。 熟练掌握 Python 以及相关机器学习 / 深度学习框架，如 PyTorch、TensorFlow、Keras 等。 精通机器学习基础设施和工具，如 Databricks、Spark、Flink、关系型数据库、AWS SageMaker、S3、EC2、Step Functions、Git。 拥有数据存储、摄取和转换方面的经验，还包括机器学习工作流程编排经验。 热衷于开发简洁、易于维护且可测试的代码。 有动力不断自我提升，探索新技术和软件服务。 对了解所在团队的业务背景以及正在解决的客户问题充满好奇并积极主动。 具备出色的沟通能力，能够将（即使是复杂的）分析 / 工程决策及成果阐释给更广泛的非技术受众。