软件工程师应届生，机器学习平台
Software Engineer New Grad, Machine Learning Platform
_[_ [_**Quora 是一家私人持有的“以远程为主”的公司**_](https://www.quora.com/q/quora/Remote-First-at-Quora) _**。** 此职位可以在加拿大或美国的任何地方远程工作。请访问_ [_careers.quora.com/eligible-countries_](http://careers.quora.com/eligible-countries) _查看各国家的雇佣资格详情。]_
### **关于 Quora：**
Quora 的使命是增长全球集体智慧。为此，我们有两个平台：
- [Quora](http://quora.com)：一个全球知识共享平台，拥有数百万月度独立访客，将人们聚集在一起，分享各种主题的见解，并提供一个独特的平台，让人们学习和与他人建立联系。
- [Poe](https://poe.com/)：一个云工作区，数百万用户在此运行多个 AI 代理，使用共享的上下文和工具。一个订阅即可访问所有前沿模型，以及使它们协同工作的协作层。
这些产品背后是充满热情、协作且高绩效的全球团队。我们有着根植于透明、想法分享和实验的文化，使我们能够通过有意义的工作庆祝成功并共同成长。加入我们，一起创造积极的影响，对世界产生重大改变。
**此职位将专注于我们的 Quora 产品。**
### **关于团队和职位：**
机器学习是 Quora 增长全球集体智慧使命的核心。我们有 100 多个机器学习模型在生产环境中运行，支持各种产品功能。我们使用多种算法——从线性模型到决策树和深度神经网络。我们的生产模型规模巨大，每月为数亿用户提供服务。
我们的团队负责 Quora 的 ML 平台和排名基础设施，涵盖四个领域：**服务可靠性、ML 工程师赋能和开发速度、业务影响以及成本效率**。我们希望赋予 Quora 所有 ML 工程师尽可能大的影响力，以解决大规模的 ML 问题。
作为该团队的 **软件工程师（应届生）**，你将在机器学习、分布式系统和 GPU 服务性能的交汇点工作——你的工作将对 Quora 的长期成功产生巨大影响。
**此职位不要求之前有 ML 基础设施经验。** 你将加入由高级和资深工程师组成的团队，从构建该技术栈的人那里学习，拥有一个
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_[_ [_**Quora is a privately held, "remote-first" company**_](https://www.quora.com/q/quora/Remote-First-at-Quora) _**.** This position can be performed remotely from anywhere in Canada or the United States. Please visit_ [_careers.quora.com/eligible-countries_](http://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](http://quora.com): 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](https://poe.com/): 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:**
Machine Learning is central to Quora's mission of growing the world's collective intelligence. We have 100+ Machine Learning models in production powering various product features. We use a variety of algorithms — everything from linear models to decision trees and deep neural networks. Our production models operate at a huge scale, serving hundreds of millions of people using Quora every month.
Our team owns Quora's ML platform and ranking infrastructure across four areas: **serving reliability, ML engineer enablement and developer velocity, business impact, and cost efficiency**. We want to empower all ML engineers at Quora to be as impactful as they can be in solving different ML problems at scale.
As a **Software Engineer (New Grad)** on this team, you'll work at the intersection of machine learning, distributed systems, and GPU serving performance — and your work will have an enormous impact on Quora's long-term success.
**No previous ML infrastructure experience is required for this role.** You'll be joining a team of senior and staff engineers, learning this stack from the people who built it, with a dedicated mentor and strong technical guidance — and you'll be shipping to production in your first few weeks.
**Stack:** Python, Go, C++, PyTorch, Kubernetes/EKS, NVIDIA Triton, Ray, AWS
🚀 Excited to see our MLP team's amazing work in action? Check out some of the incredible projects they've completed below! 👇✨
- [https://quoraengineering.quora.com/Migrating-from-x86-to-AWS-Graviton-A-Journey-in-Cost-Optimization-and-Performance](https://quoraengineering.quora.com/Migrating-from-x86-to-AWS-Graviton-A-Journey-in-Cost-Optimization-and-Performance)
- [https://aws.amazon.com/blogs/containers/quora-3x-faster-machine-learning-25-lower-costs-with-nvidia-triton-on-amazon-eks/](https://aws.amazon.com/blogs/containers/quora-3x-faster-machine-learning-25-lower-costs-with-nvidia-triton-on-amazon-eks/)
- [https://quoraengineering.quora.com/Building-a-Service-Mesh-in-a-Hybrid-Environment](https://quoraengineering.quora.com/Building-a-Service-Mesh-in-a-Hybrid-Environment)
- [https://quoraengineering.quora.com/Building-Embedding-Search-at-Quora](https://quoraengineering.quora.com/Building-Embedding-Search-at-Quora)
- [https://quoraengineering.quora.com/Feature-Engineering-at-Quora-with-Alchemy](https://quoraengineering.quora.com/Feature-Engineering-at-Quora-with-Alchemy)
### **Responsibilities:**
- Help build and maintain the core infrastructure that powers Quora's ML platform, ensuring high availability, scalability, and performance
- Build and improve the distributed systems that serve our ML models in production, from Large Recommendation Models (LRMs) to Large Language Models (LLMs)
- Work on GPU model serving, optimizing latency, throughput, and cost to support larger and more capable models
- Contribute to platform initiatives such as PyTorch-first standardization and ML ecosystem modernization
- Improve ML developer velocity by building tooling that helps ML engineers develop, test, and deploy models more efficiently
- Modernize our feature store so ML engineers can get new features into production faster
- Participate in the team's on-call rotation, helping resolve production issues as you grow your knowledge and ownership of the platform
### **Minimum Requirements:**
- **Availability for meetings and impromptu communication during Quora's "** [**coordination hours**](https://quora.com/coordination_hours) **" (Mon-Fri: 9am-3pm Pacific Time)**
- A 2025 or 2026 graduate with or pursuing a B.S., M.S., or Ph.D. in Computer Science, Engineering, or a related technical field
- Genuine interest in large-scale distributed systems, infrastructure, and machine learning
- Knowledge of Python, Go, or C++, or the ability to learn them quickly
- A passion for learning and always improving yourself and the team around you
### **Preferred Requirements:**
- Previous software engineering experience via an internship, work experience, open-source contribution, or coding competition
- Coursework or hands-on experience with ML frameworks such as PyTorch or TensorFlow
- Exposure to Kubernetes, Docker, or cloud technologies like AWS
- Experience with low-level performance work of any kind: profiling, benchmarking, optimization
- 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 $97,600 - $139,000 USD + equity + benefits.
- Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $125,320 - $142,783 CAD + equity + benefits. For all other locations in Canada, the salary range is $116,965 - $133,264 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](https://careers.quora.com/quora-global-job-applicant-privacy-notice)
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