资深机器学习工程师, 广告机器学习效率
Staff Machine Learning Engineer, Ads ML Efficiency
Reddit 是一个社区的社区。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 10 万个以上的活跃社区，以及约 1.3 亿名每日活跃的独立访客，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。
地点：Reddit 采用灵活的首要员工制度。不住在我们办公室附近？没关系：你可以在美国或加拿大任何地方远程工作。
关于团队
ML 效率团队构建基础设施、工具和优化系统，使机器学习工程师和研究人员能够高效地训练、评估、部署和运行模型。我们专注于提高开发人员的生产力，降低基础设施成本，提高硬件利用率，并加速公司 ML 生态系统中的实验。
职责
- 设计和构建提升 ML 训练和推理工作负载效率的系统。
- 开发帮助 ML 工程师调试、分析、优化和监控模型性能的工具。
- 通过调度、资源管理、缓存和工作负载优化来提高 GPU 和通用资源的利用率。
- 与 ML 研究员和产品团队合作，识别瓶颈并推动性能改进。
- 构建用于训练和服务系统的基准测试框架和性能仪表板。
- 优化分布式训练基础设施、数据管道和模型服务架构。
- 领导跨职能项目，提高 Reddit ML 工程师的生产力。
- 推动 ML 平台可扩展性、可靠性和成本效率的技术策略。
资格要求
所需条件
- 计算机科学或相关领域的学士、硕士或博士学位。
- 5 年以上软件工程经验。
- 精通 Python。
- 熟悉至少一种系统语言（Go、C++、Rust 或 Java）优先。
- 具有构建大规模分布式系统的经验。
- 具有机器学习基础设施、训练系统或模型服务平台的经验。
- 对性能工程和系统优化有深入理解。
- 强大的调试和分析技能。
优先条件
- 具有大规模推荐、排序、生成式 AI 或基础模型系统的经验。
- 具有分布式训练框架的经验
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.
Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the US or Canada.
About the Team
The ML Efficiency team builds the infrastructure, tooling, and optimization systems that enable machine learning engineers and researchers to train, evaluate, deploy, and operate models efficiently at scale. We focus on improving developer productivity, reducing infrastructure costs, increasing hardware utilization, and accelerating experimentation across the company’s ML ecosystem.
Responsibilities
- Design and build systems that improve the efficiency of ML training and inference workloads.
- Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance.
- Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization.
- Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements.
- Build benchmarking frameworks and performance dashboards for training and serving systems.
- Optimize distributed training infrastructure, data pipelines, and model serving architectures.
- Lead cross-functional initiatives that improve the productivity of Reddit ML engineers.
- Drive technical strategy for ML platform scalability, reliability, and cost efficiency.
Qualifications
Required
- BS, MS, or PhD in Computer Science or a related field.
- 5+ years of software engineering experience.
- Strong proficiency in Python
- Profiency in at least one systems language (Go, C++, Rust, or Java) preferred
- Experience building distributed systems at scale.
- Experience with machine learning infrastructure, training systems, or model serving platforms.
- Deep understanding of performance engineering and systems optimization.
- Strong debugging and profiling skills.
Preferred
- Experience with large-scale recommendation, ranking, generative AI, or foundation model systems.
- Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark
- Familiarity with GPU architectures and performance analysis tools.
- Experience optimizing cloud infrastructure costs across large ML workloads.
- Contributions to internal platforms used by multiple ML teams.
- Experience with building real time ML inference applications
What Success Looks Like
- ML engineers can move from idea to experiment faster.
- Training and inference costs decrease, performance increases, while model quality is maintained or improved.
- GPU utilization and cluster efficiency increase.
- Platform reliability improves as ML workloads scale.
- Teams spend less time managing infrastructure and more time building models.
- Average recommendation model size increases.
Benefits:
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Group Personal Pension Scheme with Employer match
- Private Medical and Dental Scheme
- Income Replacement Programs
- Bike to Work scheme
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
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.