京东Machine Learning Engineer
任职要求
Minimum Qualifications: - Bachelor's degree in Engineering, Computer Science, Mathematics, or a related technical field. - Professional experience in software development, with recent years focused on search technologies. - Professional experience in testin…
工作职责
Responsibilities: - Participate in system design, architecture, and software development of the search and recommendation function. - Design, develop, test, deploy, maintain, and enhance high-quality code and solutions. - Perform code reviews to optimise the technical performance of the solutions. - Influence and coach a distributed team of engineers.
1. 负责国际业务场景下的机器学习算法研发与优化，通过深入理解业务需求，设计并实现高效、精准的算法模型，以提升业务智能化水平； 2. 依据业务发展需求，承担算法框架的设计与开发，确保算法的准确性、稳定性与可扩展性，并通过技术手段解决实际业务痛点； 3. 跟踪并研究机器学习领域的前沿技术，负责将先进技术应用于实际项目中，推动业务流程的优化与创新； 4. 与团队成员紧密协作，通过跨部门沟通，确保项目顺利推进，达成业务目标； 5. 负责算法模型的持续迭代与效果评估，建立完善的监控与优化机制，保障算法在业务场景中的稳定落地与持续改进； 6. 日常在英国伦敦办公室工作。
Design and build infrastructures to support features that empowers billions of Siri, Spotlight, and Safari users. Perform language processing, statistical analysis, and user intent analysis to support your hypothesis for how to improve product-outcomes. Leverage proprietary parallel data processing platform to process web scale data to deliver product features and improvements. Design & run/deploy various metrics and evaluations of features/improvements using a variety of tools like grading, logs processing, pre-launch and holdback A/Bs. Present results of analysis to team and leadership across Apple.
As a Machine Learning Engineer, you will be entrusted with the critical role of innovating and applying state-of-the-art technology in foundation models to tackle complex problems. The solutions you develop will significantly impact future Apple products and the broader ML development ecosystem. You will work with a multidisciplinary global team to actively participate in the data-modeling-evaluation co-design and co-development practice. Your responsibilities will extend to the design and development of data curation pipelines, advanced modeling methodologies and effective evaluation metrics. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues.
Design, develop, and optimize core machine learning models and data architectures to support manufacturing processes. Develop advanced multimodal and LLM-based models for hardware test reasoning and analysis. Integrate core ML capabilities into central frameworks, ensuring seamless end-to-end functionality and system optimization. Collaborate with cross-functional teams to validate, debug, and deploy production-ready algorithms to real-world factory infrastructures.