ASMLAlgorithm Engineer
任职要求
Master degree with solid experience, or equivalent working and thinking level. Experienced practitioner, able to work unsupervised. In-depth knowledge of own complex tasks or simple sub-module within own area of expertise and Basic knowledge of neighboring parts / areas of expertise within module and basic module and system knowledge Mono disciplinary knowledge Basic knowledge of how own sub-system interacts to other sub-systems Responsibilities Research Carry out a range of research activities either to support others or to fulfill the requirements of the role. Design Requirements and specifications Plan and coordinate the identification, elicitation of requirements, conduct analysis of those requirements for completion and alignment, document and manage requirements throughout the life of the project and coordinate the verification of the end deliverable. Generally done at the project level. Feasibility Contribute to and support feasibility studies from a technological and organizational perspective, and document findings. Conceptualization Contribute to the design of engineering solutions; design the feasibility testing approach and supervise its implementation to support the development and validation of engineering solutions. Preliminary design Develop technical concepts including material choices. Make technical choices in all phases, solve technical issues, devise new approaches to problems encountered. Prepare high level design of the (sub-) module fulfilling the requirements set while addressing architectural and interface choices. Document the high level design in the relevant SEG documents. Detailed design Contribute to the design of engineering solutions; design the feasibility testing approach and supervise its implementation to support the development and validation of…
工作职责
Context Leads a complex technical design or has ownership of a module that requires contribution from several engineers. Starts thinking about modules / influences other parts of modules; oversees several components that are linked (module). Leading on mono-disciplinary designs / projects, taking industrialization into account. Works with engineers of teams of adjacent /collaborating FCs/ICs, interfaces within team of a train or multiple products. Interfaces with suppliers or customers as member of a larger team. Looks at problems from multiple known angles and proposes different ‘out of the box’ solutions to choose from, in an environment with technical uncertainty. Balances between quality and timely delivery. Acts autonomously in own area of expertise, working independently on complex design engineering tasks, defines design solution. Works towards given results, with freedom to decide how to realize these. Independently applies and adheres to quality standards (e.g. D&E handbook). Guides 1-2 engineers in development of specific part or module. Designs, develops, tests and integrates software for ASML’s machines and applications. Implements analytics, data, control and algorithms applications that give ASML customers the power to reach optimal performance during manufacturing.
1、参与亿级用户规模的电商推荐优化,提升内容电商观看时长、点击率、转化率、GMV、LTV等核心指标; 2、通过深度学习领域的研发工作,包括但不限于深度模型设计与优化、强化学习、迁移学习、图神经网络等的算法和系统提升预估效果; 3、通过推荐算法机制优化电商流量结构和GMV结构,促进电商生态的健康发展。
1、参与亿级用户规模的电商推荐优化,提升包括商品推荐(首页猜你喜欢)、内容推荐(直播、短视频)在内的泛货架电商的GMV、订单量、用户留存等核心指标; 2、通过深度学习领域的研发工作,包括但不限于生成式推荐、LLM4Rec、超大规模序列建模、多任务学习、长期价值建模等算法和系统提升预估效果; 3、持续关注前沿技术发展方向,参与推荐系统架构的长期技术演进与技术攻坚; 4、通过推荐算法机制优化电商流量结构和GMV结构,促进电商生态的健康发展。
1、负责快手国际化Push相关的算法研发、优化工作,运用策略和算法手段促进用户增长; 2、负责Push推荐系统的搭建以及相关算法落地,面对亿级别的用户群体情况下实现Push的个性化匹配,做到千人千面; 3、负责Push的算法、策略的设计,并直接参与Push场景下推荐系统的全链路开发与优化,包括但不局限于触发、召回、粗排、精排、下发策略等阶段; 4、从海量数据中挖掘用户消费行为、社交关系网以及运营热点实现Push内容池的搭建。
We are aiming to leverage AI and other leading technology and dedicated to provide safe and reliable risk control capabilities behind payments. The core technologies include rule engines, model engines, intelligent algorithm models, etc., We are the leading platform with capabilities of high concurrent real-time risk calculations and massive big data analysis and processing. And as the core risk management tech platform for global payment business, we adopt a multi-center deployment architecture around the world. Here you may have the opportunity to learn more about and participate in the design and development of the following aspects: 1. Ultimate computing optimization at the millisecond level. 2. Behavior analysis and risk mining under massive data. 3. Global multi-center system architecture planning and high-availability solution design. 4. Participated in the design of R&D of risk control systems and big data platforms. You will also have the opportunity to explore the architectural design and implementation of cutting-edge technologies such as privacy computing and large models in risk control systems.