Machine Learning Tech Lead - Feed Personalization, Quora (Remote)

[Quora is a privately held, "remote-first" company. This position can be performed remotely from multiple countries around the world. 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 over 300M 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 platform providing millions of global users with one place to chat, explore and build with a wide variety of AI language models (bots), including GPT-5.2, Claude Opus 4.5, Grok 4.1, Veo 3.1, Nano Banana Pro (Gemini 3 Pro Image), and more. As AI capabilities rapidly advance, Poe provides a single platform to instantly integrate and utilize these new models.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 small engineering team works on challenging problems every day. We have a culture that's rooted in constantly learning and improving, and our engineers are encouraged to think big and experiment with new ideas. As a remote-first company, our engineers have a high degree of flexibility and autonomy. Everyone on the engineering team has a significant impact on our product and our company. We are looking for an experienced Machine Learning engineer to join our growing engineering team, working on recommendation systems such as feed, notifications, and Quora’s famous digest emails and A2A. At Quora, we use machine learning in almost every part of the product and recommendation systems play an important role in connecting users with content.As a recommendation systems expert, you will have a unique opportunity to have high impact by advancing our ranking systems as well as uncovering new opportunities to apply machine learning to the Quora product. You will also play a key role in developing tools and abstractions that our other developers will build on top of.Responsibilities:Improve our existing machine learning systems using your core coding skills and ML knowledgeIdentify new opportunities to apply machine learning to different parts of the Quora productWork with other machine learning engineers to implement algorithms and systems efficientlyTake end-to-end ownership of machine learning systems - data pipelines, candidate extraction, feature engineering, model training, as well as integration into our production systemsMinimum Requirements:Availability for meetings and impromptu communication during Quora's “coordination hours" (Mon-Fri: 9am-3pm Pacific Time)7+ years of professional software development experience in machine learning4+ years of professional experience building and optimizing Home Feed recommendation systems for social media and user-generated content platforms.Good understanding of mathematical foundations of machine learning algorithmsPrevious experience building end-to-end machine learning systems.Good communication and interpersonal skillsBS, MS, or PhD in Computer Science, Engineering, or a related technical fieldPreferred Requirements:Experience writing Python or C++ codeExperience with leading large-scale multi-engineer projectsPassion for Quora's mission and goalsAt 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 ap ... (truncated, view full listing at source)