资深机器学习系统工程师
Staff Machine Learning Systems Engineer
Reddit 是一个由社区组成的社区。它建立在共同的兴趣、热情和信任之上,是互联网上最开放和真实的对话场所。每天,Reddit 用户提交、投票并评论他们最关心的话题。拥有 100,000 多个活跃社区,以及大约 1.3 亿日活跃独立访客,Reddit 是互联网上最大的信息来源之一。更多信息,请访问 www.redditinc.com。
我们是谁:
Reddit 的机器学习平台团队是一个高影响力的团队,负责支持推荐、内容发现、用户和内容量化等功能的基础设施,并直接影响增长、广告、信息流和核心机器学习团队。
你将做什么:
作为资深机器学习基础设施工程师,你将领导 Reddit 大规模机器学习模型平台的开发。
- 设计端到端的模型生命周期模式(MLOps),以提升机器学习工程师的开发速度,包括数据准备、模型管理、实验跟踪等
- 从零开始开发和维护一个图机器学习代码库和平台,抽象出常见模式,实现更高的模型可扩展性和迭代能力
- 与机器学习工程师合作进行性能调优,包括提高模型训练时间、效率和大规模分布式机器学习训练环境中的 GPU 训练成本
- 优化数据仓库中的批量数据处理,使用 Apache Beam、Apache Spark、Ray Data 等工具
- 架构管道以构建和维护数十亿节点和数百亿边的大规模图数据结构
你可能具备:
- 8 年以上机器学习基础设施经验,包括模型训练和模型部署
- 具有机器学习优化的实际经验,包括内存和 GPU 分析
- 在支持机器学习平台的云技术方面有深入经验,包括 GCP BigQuery、Google Cloud Storage、基础设施即代码(Terraform)等工具
- 具有管理并集成 MLOps 工具的实际经验,用于实验跟踪、模型服务和模型注册表(如 MLflow 或 Wandb)
- 熟练掌握常见的机器学习编程语言和框架,如 Python、PyTorch、TensorFlow 等
- 在分布式训练框架方面有深入经验,包括 Ray 和 Kubernetes
- 强调可扩展性、可靠性、性能和易用性。你是持续推动改进的倡导者
查看英文原文
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.
Who We Are:
The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams.
What You’ll Do:
As a Staff ML Infrastructure Engineer, you will lead development of a platform for large scale ML models at Reddit.
- Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more
- Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration
- Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment
- Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more
- Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges
Who You Might Be:
- 8+ years of experience in ML infrastructure, including model training and model deployments
- Hands-on experience with ML optimization, including memory and GPU profiling
- Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more
- Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb)
- Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc.
- Deep experience working with distributed training frameworks, including Ray and Kubernetes
- Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle.
- Strong organizational & communication skills
- Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus
- Experience working with graph neural networks (GNNs) and associated graph ML frameworks (PyTorch Geometric, Deep Graph Library) is a big plus
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base salary range for this position is:
$230,000—$322,000 USD
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.