远程工作雷达

资深机器学习工程师,消费者

Staff Machine Learning Engineer, Consumer

AI开发工程限定地区(需当地身份)
公司Reddit
薪资未公开
工作地点Remote - United States
地域资格限定地区(需当地身份)
时区要求无特别要求
用工类型未标注
发布时间2026-03-24
数据来源Greenhouse
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注意地域限制:该职位明确限定在 Remote - United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

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。如需更多信息,请访问 www.redditinc.com。

在 Reddit,机器学习是数百万用户发现、连接和参与世界上最大人类对话集合的核心。从推动个性化推荐和搜索,到优化广告系统和市场动态,我们的 ML 工程师解决大规模应用机器学习中最具挑战性和影响力的问题。

我们正在招聘消费工程团队的机器学习工程师,让你有机会在消费生态系统中广泛参与高影响力的问题。我们寻找对从研究和建模到生产部署构建系统充满热情的机器学习工程师,并希望帮助塑造 Reddit 的发现、相关性和变现的未来。

如果你热爱在大规模环境下解决复杂的真实世界机器学习问题,这个职位适合你。

你将参与的工作

我们正在寻找一位资深机器学习工程师,以推动 Reddit 在推荐、搜索、消息传递和基础 AI 系统方面的下一代 ML 生态系统。你将从构思到生产领导高影响力项目,塑造多个 ML 领域的技术战略和产品方向。这是一个高度跨职能的角色,与产品、数据科学和工程团队合作,实现有意义的用户体验和商业影响。

该职位位于以下领域的交汇点:

  • 相关性与推荐系统(内容、搜索、通知)
  • AI 驱动的发现与大语言模型驱动的体验
  • 内容和用户理解与大规模表示学习
  • 大规模 ML 基础设施和流水线

你将做的事情

  • 从构思到生产及迭代,领导端到端的 ML 项目,塑造技术方向,并将产品目标转化为可扩展的解决方案
  • 设计、构建和部署大规模 ML 系统,涵盖推荐、搜索和内容/用户理解,包括检索/排序模型、表示学习等
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.

At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning.

We are hiring Machine Learning Engineers across our Consumer Engineering organization, giving you the opportunity to work on a wide range of high-impact problems across the Consumer ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, and who want to help shape the future of discovery, relevance, and monetization at Reddit.

If you love working on complex, real-world ML problems at massive scale, this role is for you.

What You’ll Work On

We are looking for a Staff Machine Learning Engineer to help drive the next generation of Reddit’s ML ecosystem across recommendations, search, messaging, and foundational AI systems. You will lead high-impact initiatives from ideation to production, shaping both technical strategy and product direction across multiple ML domains. This is a highly cross-functional role partnering with Product, Data Science, and Engineering to deliver meaningful user and business impact.

This role sits at the intersection of:

  • Relevance & recommendation systems (content, search, notifications)
  • AI-powered discovery & LLM-driven experiences
  • Content and user understanding & large-scale representation learning
  • Large-scale ML infrastructure and pipelines

What You’ll Do

  • Lead end-to-end ML initiatives from ideation through production and iteration, shaping technical direction and translating product goals into scalable solutions
  • Architect, build and deploy large-scale ML systems across recommendation, search, and content/user understanding, including retrieval/ranking models, representation learnings embeddings optimizations, and LLM or GenAI-powered capabilities
  • Drive measurable impact on user engagement, discovery, and long-term value
  • Collaborate with cross-functional teams to align product and technical roadmaps and unlock key future ML capabilities
  • Stay at the forefront of AI research, evaluating and introducing new AI/ML paradigms to keep Reddit’s ML ecosystem at the cutting edge
  • Contribute to the development of best practices, guidelines, and ethical AI principles for responsible LLM development and deployment
  • Mentor and guide senior and mid-level ML engineers, fostering a culture of excellence, innovation, and knowledge sharing
  • Set technical vision and drive technical discussions, present findings to leadership, and contribute to long-term ML planning and decision-making

Required Qualifications

  • 7+ years of experience building, deploying, and operating machine learning systems in production
  • Deep understanding of machine learning methods, spanning classical approaches and modern deep learning (e.g., Transformers, GNN, etc)
  • Expert at developing and productionizing models using TensorFlow, PyTorch, or Hugging Face Transformers
  • Experience building production-quality code incorporating testing, evaluation, and monitoring using object-oriented programming, including experience in Python and Golang
  • Experience designing and scaling ML systems, including data pipelines, feature engineering, model training/serving, and production monitoring
  • Excellent communication and collaboration skills, with the ability to discuss complex technical topics with diverse teams and translating product needs into scalable ML solutions
  • Track record of driving measurable impact through applied machine learning in real-world products

Preferred Qualifications

  • Subject matter expertise in one of the following domains:
  • Recommender systems
  • Search systems (lexical and semantic retrieval and ranking)
  • Content understanding (NLU/NLP/LLM, topic/taxonomy modeling, interest graphs or clustering, and multimodal understanding)
  • Familiarity with distributed systems and large-scale data processing frameworks (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
  • Experience working with real-time systems and low-latency production environments
  • Experience with LLM/GenAI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale
  • Strong experimentation rigor, with experience formulating clear hypotheses, designing actionable learning plans and building offline/online correlations
  • Advanced degree in Computer Science, Machine Learning, or related quantitative field

Potential Teams

  • Home Experience
  • ML Understanding
  • Feed Relevance
  • Answer Experience
  • Search and Answers Relevance
  • Search Experience

Benefits

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k with Employer Match
  • 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
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave

#LI-Remote

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.

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