出海雷达

Machine Learning Engineer, Answers Relevance

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
发布时间昨天
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。
关于本页中文:职位描述由本机离线模型翻译,属机器翻译,供快速判断用;正式沟通与投递请以英文原文为准。官方翻译通道恢复后会自动重译升级。

网易博客是社区的社区。它建立在共同利益,激情和信任之上,也是互联网上最开放且真实的对话所在地。每天,Reddit 用户提交,投票,评论他们最关心的话题。拥有超过10万个活跃社区和约13000万名每日活跃的独特访问者,Reddit 是互联网最大的信息来源之一。更多信息请参观 www.redditinc.com. 在 Reddit,机器学习是数百万人的发现,连接和参与世界最大的人类交谈的核心。从我如何修复漏水龙头?到我要接下来看什么?,答案相关性团队利用 AI 将人们与 Reddit 社区的现实世界智慧联系起来。我们正在聘请高级和工作人员机器学习工程师,使答案变得更智能,更有关联和更有用。我们的 SOTA AI 系统帮助表现出正确的对话,但答案的核心仍然是帮助人们分享他们知道的事情!你会从想法到生产,与产品合作,数据科学和工程建议,搜索,通讯和人工智能系统。你不需要在以下列出的每个领域都有经验。仅有的背景可能会让你非常适合!· 推,搜索,内容理解或大规模数据和 ML 基础设施 · SOTA 大规模 RecSys · 基本检索模型 · RAG 系统,检索方法,LLM 评估或生产 LLM 功能 · 代理 AI,如工具调用,MCPs,多代理系统或配套 · 自主托管的开放权重模型如 Qwen 或 Llama;快速工程,细节调整,后培训或快速优化 ·改善地面接地,遵循指令和幻觉;评估检索和生成 · 加容 LLM 系统,包括延迟,缓存和成本;快速注射和不安全输入的安全措施 ·定义产品成功指标,反循环以及评估方法,包括人体审查 你将做什么 ·建立和改进大型 ML 系统,包括检索和排名,嵌入式和 LLM 驱动功能 ·设定技术方向并提供可测量用户和业务影响 ·与合作团队一起塑造产品和技术路线图 ·评估新的 AI/ML 方法并支持负责 LLM 开发 ·辅导工程师和管理人员

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 “How do I fix a leaky faucet?” to “What should I watch next?”, the Answers Relevance team leverages AI to connect people with the real-world wisdom of Reddit communities. We’re hiring Senior and Staff Machine Learning Engineers to make Answers smarter, more relevant, and more helpful. Our SOTA AI systems helps surface the right conversations, but the heart of Answers is still people helping people ~ Redditors sharing what they know with each other!

What You’ll Work On
You’ll lead ML projects from idea to production, partnering with Product, Data Science, and Engineering across recommendations, search, messaging, and AI systems.

You don’t need experience in every area listed below. A background in a few may make you a great fit!

  • Recommendations, search, content understanding, or large-scale data and ML infrastructure
  • SOTA large scale RecSys
  • Foundational retriever models
  • RAG systems, retrieval methods, LLM evaluation, or production LLM features
  • Agentic AI, such as tool calls, MCPs, multi-agent systems, or orchestration
  • Self-hosted open-weight models such as Qwen or Llama; prompt engineering, fine-tuning, post-training, or prompt optimization
  • Improving grounding, instruction following, and hallucination; evaluating retrieval and generation quality
  • Scaling LLM systems, including latency, caching, and cost; safety measures for prompt injection and unsafe inputs
  • Defining product success metrics, feedback loops, and evaluation approaches, including human review

What You’ll Do

  • Build and improve large-scale ML systems, including retrieval and ranking, embeddings, and LLM-powered features
  • Set technical direction and deliver measurable user and business impact
  • Work with partner teams to shape product and technical roadmaps
  • Evaluate new AI/ML approaches and support responsible LLM development
  • Mentor engineers and contribute to long-term ML planning

Required Qualifications

  • 4–12 years of experience building, deploying, and operating ML systems in production
  • Broad knowledge of ML fundamentals and experience applying them in production; expert-level modeling depth isn’t required
  • Experience developing and productionizing models with TensorFlow, PyTorch, or Hugging Face Transformers
  • Experience writing production-quality code, including testing, evaluation, and monitoring; Python experience required, Golang experience a plus
  • Experience with ML systems such as data pipelines, feature engineering, model training and serving, and production monitoring
  • Strong communication and collaboration skills, and a record of delivering measurable product impact

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:
$216,700—$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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