

Snap 的机器学习工程
作为 Snap 的机器学习工程师,您将推动 Snapchat 的动态体验,参与最先进模型的整个生命周期,从数据预处理、特征工程和模型训练,到部署和持续优化。 您将利用尖端技术、广告相关性排名算法、个性化内容推荐引擎和用于增加互动性的自然语言处理, 同时处理超过 8.5 亿用户的 PB 级数据。
通过经典和深度学习模型,您将创造精确、响应迅速的体验,让用户能够实时表达自我、建立联系和探索世界。
探索我们的团队
我们的机器学习工程师致力于解决现实世界的机器学习问题。

创收
作为创收团队的机器学习工程师,你将构建和优化整个广告生态系统。 你将不仅为广告商和用户,而且为整个 Snap 带来高相关性和高影响力。从为实时竞价或广告投放和竞价设计高性能系统,到对轻量级和重量级排名器进行个性化定制,再到为广告定向投放制定解决方案,你将持续确保广告在整个平台上无缝集成。 你将使用多任务学习、序列建模和用户与广告互动建模,在数十亿个示例上训练模型。 我们的模型通过图形神经网络和内容来预测用户的受众特征,以优化受众定位,从而了解我们的工作如何塑造 Snapchat 广告平台的未来。
你将致力于以下工作:
AI 驱动的广告
全新的个性化广告产品和体验
Snap 主要收入驱动力的所有者
开发前沿广告产品
Interview Process
Below is an overview of the interview rounds and competencies that may be assessed throughout the ML interview process. Depending on your target level, the order of these rounds may differ or you might have some rounds omitted. Each technical interview will begin with approximately 15 minutes of behavioral discussion focused on experiences aligned with Snap’s values. Following your answer, your interviewer will transition into the technical portion of the interview assessing one of the below competencies:
我们正在招聘!
我们的面试流程涵盖工程、基础和应用机器学习。
编码
您需要解决算法问题,以测试您在数据结构、算法和解决问题方面的熟练程度。重点考察您编写清晰、高效、文档齐全的代码的能力。
机器学习基础
您将接受机器学习理论和核心机器学习模型、概念、技术和应用的评估。准备好讨论监督和非监督学习、推荐系统、排名、模型评估指标和优化技术。
机器学习应用设计
评估您设计和应用机器学习解决方案来解决实际问题的能力。您可能会被要求完整地介绍选择模型、特征工程和评估性能的端到端过程。有时,这可以测试您在模糊环境中解决问题的能力。
机器学习系统设计
重点将是设计可扩展且稳健的机器学习系统,以处理大规模数据和生产环境。准备好讨论基础设施、架构中的权衡、模型部署策略和系统监控。
General Coding
This will be focused on general computer science fundamentals. You can expect algorithms and data structure question(s) for this round and you are able to code in your language of preference.
Leadership
Depending on the target level, candidates may participate in a leadership interview focused on collaboration, influence, ownership, communication, mentorship, and decision-making. Interviewers will assess how you navigate ambiguity, drive impact across teams, and support effective engineering practices, including thoughtful adoption of AI-assisted workflows, through examples from your past experience.
Product
This round is required for L6+ interviews and will be conducted by a Product Manager or an ML Engineer. The objective is to assess your ability to understand customer needs, build business domain knowledge, bridge technical ML solutions and product requirements, and partner cross-functionally with Product Managers.
Q&A
The Q&A session will not include any formal technical or behavioral competency assessment like other rounds. Instead, it is an opportunity for candidates to learn more about the team, projects, and company. Candidates are encouraged to come prepared with thoughtful questions about the role, team culture, technical challenges, cross-functional collaboration, growth opportunities, or life at Snap.




