苹果Machine Learning Engineer, Computer Vision Algorithm (Video Object Detection and Tracking)
任职要求
Minimum Qualifications • M.S. or PhD in Electrical Engineering/Computer Science or a related field (mathematics, physics or computer engineering), with a focus on computer vision and/or machine learning • Rich experiences in machine learning and computer vision, covering one of the topics: Video Object Detection / Video Object Tracking / Depth Estimation / Neural Architecture Search • Proven prototyping skills and proficient in coding (C, C++, Python) • Excellent written and verbal communications skills, be comfortable presenting research to large audiences, and have the ability to wo…
工作职责
The computer vision algorithm engineer will work in a dynamic team as part of the Video Computer Vision org. which develops on-device computer vision and machine perception technologies across Apple’s products. We balance research and product to deliver the highest quality, state-of-the-art experiences, innovating through the full stack, and partnering with cross-functional teams to influence what brings our vision to life and into customers hands.
1、负责搭建快手NLP技术体系，包括但不限于文本分类、知识图谱、翻译、对话等； 2、与业务部门进行沟通与协作，交付满足产品需求的核心算法模型与能力。
1、负责AI小快智能助理机器人的研究和开发； 2、优化基础模型，并采用RAG、Agent等大模型衍生框架，来提升相关业务指标； 3、持续跟进并深入调研大模型前沿技术、开源方案，跟踪业内大模型领域的最新进展并推进相关研究，探寻将最新技术应用到AI小快的可能性。
1、模型研发与优化： 负责从0到1构建和迭代机器学习/深度学习模型（如：异常检测、图神经网络、自然语言处理、时间序列分析等），应用于恶意代码分类、网络入侵检测、用户行为分析、钓鱼网站识别等具体场景； 2、威胁狩猎与研究： 利用机器学习模型发现未知威胁和攻击模式，参与安全事件的分析与响应，为安全策略的制定提供数据驱动的洞察； 3、大模型智能体的落地：探索大模型结合信息安全领域的应用，如攻击告警自动化处理等； 4、数据探索与特征工程： 深入分析海量安全数据（如日志、流量、恶意样本、威胁情报等），进行数据清洗、特征提取和特征工程，为模型训练提供高质量的数据基础； 5、前沿技术探索： 跟踪学术界和工业界在AI安全领域的最新进展，评估并将有潜力的新技术（如：联邦学习、对抗机器学习、自监督学习等）应用于实际业务，解决诸如样本稀缺、对抗性攻击等挑战。
1. Lead the planning and execution of the e-commerce platform's search product to enhance the relevance of search results and improve user experience. 2. Analyze user search behavior and data to identify optimization opportunities and improve search algorithms accordingly. 3. Collaborate with technical teams to drive the development and optimization of the search engine, including the application of natural language processing and machine learning technologies. 4. Develop and manage the search product roadmap, ensuring timely delivery of projects that meet quality standards. 5. Monitor key performance indicators of the search system, providing regular analysis reports and improvement suggestions. 6. Work closely with product, marketing, and user experience teams to ensure that search product functionalities align with the overall strategy.