寻找你的下一个职业机会

按职位、技能和地点搜索招聘信息。准备申请前,先仔细了解职位要求。

找到一个吸引人的职位名称只是求职的起点。请将工作职责、招聘要求和工作条件与你的实际经历进行比较。本指南帮助你筛选机会、准备有针对性的申请材料,并确认每份申请应该在哪里提交。

此界面为简体中文。雇主发布的职位名称和描述保留原文,可能为英文。

清除筛选

搜索结果: 14,087

← 返回搜索结果

Machine Learning Engineer, New Grad - Quora (Remote)

quora

远程工作

地点
Remote - Multiple Locations
工作安排
FullTime
发布日期
2026年10月15日

申请前,请在雇主网站确认职位仍在招聘,并检查完整要求和条件。

职位描述

此界面为简体中文。雇主发布的职位名称和描述保留原文,可能为英文。

[Quora is a privately held, "remote-first" company. This position can be performed remotely from anywhere in the US or Canada. Please visit careers.quora.com/eligible-countries for details regarding employment eligibility by country.] About Quora: Quora’s mission is to grow the world's collective intelligence. To do so, we have two platforms: Quora: a global knowledge sharing platform with millions of monthly unique visitors, bringing people together to share insights on various topics and providing a unique platform to learn and connect with others. Poe: a cloud workspace where millions of users run multiple AI agents on shared context and tools. One subscription, every frontier model, and the collaboration layer that makes them work together. Behind these products are passionate, collaborative, and high-performing global teams. We have a culture rooted in transparency, idea-sharing, and experimentation that allows us to celebrate success and grow together through meaningful work. Join us on this journey to create a positive impact and make a significant change in the world. This role will be working on our Quora product. About the Team and Role: Our ML team is small and highly collaborative, working on challenging problems that impact hundreds of millions of Quora users. We encourage engineers to think big, experiment with new ideas, and continuously learn and improve. With over 100 ML models in production, engineers have opportunities to take ownership of meaningful projects, work closely with experienced teammates, and quickly see the impact of their work. We're building the next generation of AI-powered systems to improve content quality and safety across Quora. By leveraging LLMs and agentic workflows, we're transforming how we detect harmful content, automate complex decisions, and respond to evolving challenges at scale. As a Machine Learning Engineer (New Grad), you'll work alongside experienced engineers to design, evaluate, and deploy these systems in production. No previous trust and safety experience is required. You'll learn from the engineers who built these systems. Stack: Python, PyTorch, TensorFlow, Spark, Kubernetes Responsibilities: Design, build, and deploy LLM-powered agents to detect and address spam, harassment, and other policy-violating content at Quora's scale Develop agentic workflows to automate complex tasks, improving the efficiency and effectiveness of our content and user moderation systems Design and improve ML systems that adapt to evolving abuse patterns and new challenges Evaluate agent performance through offline evaluations, online experiments, and production monitoring, balancing accuracy, reliability, latency, and cost Investigate failure cases, experiment with new approaches, and iterate on solutions to improve system performance Identify new opportunities to apply ML and LLMs to content quality and safety across Quora Collaborate with experienced engineers and take ownership of projects from early development through production Minimum Requirements: Availability for meetings and impromptu communication during Quora's “coordination hours" (Mon-Fri: 9am-3pm Pacific Time) B.S., M.S., or Ph.D. in Computer Science, Engineering or a related technical field, completed or in progress Strong understanding of mathematical foundations of Machine Learning algorithms Coursework, research, or project experience with LLM applications or transformer models Strong knowledge of Python A passion for learning and always improving yourself and the team around you Able to start full-time in early 2027 Preferred Requirements: Previous software engineering experience via an internship, work experience, open-source contribution or coding competition Hands-on experience building and evaluating LLM agents, in projects, research, internships, or production Regular use of AI coding tools such as Claude Code or Codex Coursework or projects in natural language processing (NLP) Genuine interest in content safety and quality Passion for Quora's mission and goals At Quora, we value diversity and inclusivity and welcome individuals from all backgrounds, including marginalized or underrepresented groups in tech, to apply for our job openings. We encourage all candidates who share a passion for growing the world’s knowledge, even those who may not strictly meet all the preferred requirements, to apply, as we know that a diverse range of perspectives can have a significant impact on our products and our culture. Additional Information: We are accepting applications on an ongoing basis. This role is a backfill for an existing vacancy. Quora offers a wide range of benefits including medical/dental/vision coverage, equity refreshers, remote work reimbursement, paid time off, employee assistance programs, and more. Benefits are country-specific and may vary. There are many factors that will determine the starting compensation, including but not limited to experience, location, education, and business needs. US candidates only: For US based applicants, the salary range is $107,360 - $152,900 USD + equity + benefits. Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $137,852 - $157,061 CAD + equity + benefits. For all other locations in Canada, the salary range is $128,661 - $146,590 CAD + equity + benefits. In equity-eligible countries, we currently also offer a flexible equity program where a portion of equity compensation may be taken as cash. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. AI technology may assist in sorting applications and recording interview notes, but all decisions are made by a member of our team. To ensure a secure hiring process, all final candidates will undergo identity verification and a comprehensive background check prior to onboarding. Job Applicant Privacy Notice: https://careers.quora.com/quora-global-job-applicant-privacy-notice #LI-JC1 #LI-REMOTE

查找职位、比较要求,再准备申请

从你希望从事的职位或运用的技能开始搜索。调整地点和职业筛选,打开职位比较工作职责。如果没有结果,可以使用更短的关键词,或逐一移除筛选条件。

区分必备要求和优先条件,检查已列出的工作安排、薪资和地点。远程职位也可能要求特定居住国家、工作许可或工作时间重合。请向雇主确认职位信息和完整条件。

选择能够回应职位要求的真实经历,说明你的贡献,只使用能够证实的数字。遵循雇主的申请说明,并在提交前检查联系方式、文档内容和 PDF。

提交申请前的检查清单

求职常见问题

为什么有些职位使用英文?

职位名称和描述由招聘企业撰写。为避免改变招聘要求或工作条件,我们保留原文。操作界面和本指南使用简体中文。如果中文搜索没有结果,可以尝试使用职位发布语言中的名称或技能,例如“software engineer”。搜索词不会自动翻译,界面语言也不代表企业要求的申请语言。

远程职位是否允许从任何国家工作?

不一定。企业可能对居住国家、工作许可或工作时段有要求。请查看原始招聘页面中的具体条件。如果未说明,应先向企业确认,再判断能否从你所在的地区工作。“远程”标签本身并不代表没有地点限制。

搜索没有结果时应该怎么办?

尝试更通用的职位名称或单个技能,并逐一移除筛选条件。不同企业可能用不同名称描述相似工作。如果某个职位已经消失,请在企业招聘页面搜索其职位编号。扩大搜索范围不会让已经关闭的职位重新开放。

申请会通过 ResumizeAI 直接提交吗?

申请按钮会打开外部网站。请按照企业或招聘服务的说明,在该网站完成并确认提交。在 ResumizeAI 中准备简历并不等于已经申请职位。如果链接只打开企业网站,请先找到对应职位,再继续申请流程。

如何针对职位调整简历和求职信?

将招聘要求与能够解释清楚的项目、任务和成果联系起来。突出相关经历,不要添加未经实际掌握的技能或虚构成绩。在求职信中用具体例子说明申请动机,并遵守企业要求的语言和文件格式。提交前检查两份文件,确保内容准确、联系方式正确、链接可用。