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[ Quora is a privately held, "remote-first" company . This position can be performed remotely from anywhere in Canada or the United States. 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: 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://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-Embedding-Search-at-Quora - 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 " (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://www.careers.quora.com/pages/quora-global-job-applicant-privacy-notice #LI-SS2 #LI-REMOTE

[ Quora is a privately held, "remote-first" company . This position can be performed remotely from anywhere in Canada or the United States. 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: 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://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-Embedding-Search-at-Quora - 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 " (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://www.careers.quora.com/pages/quora-global-job-applicant-privacy-notice #LI-SS2 #LI-REMOTE

[ Quora is a privately held, "remote-first" company . This position can be performed remotely from anywhere in Canada or the United States. 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: 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://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-Embedding-Search-at-Quora - 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 " (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://www.careers.quora.com/pages/quora-global-job-applicant-privacy-notice #LI-SS2 #LI-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 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 Monetization team works on challenging problems every day. Our Machine Learning Engineers are tasked with optimizing the advertising product at Quora, and the team covers the entire Machine Learning Ads lifecycle from end-to-end, including ads targeting, ranking and auction dynamics, and quality measurement. Ingrained in our culture is the desire to constantly learn and improve, and our engineers are encouraged to think big and experiment with new ideas. Using continuous deployment, we quickly see our changes in the product and make fast iterations. As a remote-first company, our engineers have a high degree of flexibility and autonomy, and everyone on the engineering team has a huge impact on our product, revenue and company. Since we first launched our advertising platform, we've grown to support thousands of advertisers who are reaching over 300 million+ monthly unique visitors on Quora. Our journey is just beginning as we continue to build new products from the ground up and tackle exciting challenges at scale. We are looking for an experienced Machine Learning Engineer to join the Ads ML team as an ads ranking specialist. You will improve CTR and CVR prediction, model calibration, user and ad representations, and user-sequence modeling, translating improvements in ranking quality into measurable advertiser value, revenue, and better user experiences. This is a small, close-knit team where you own problems end-to-end — research, data, modeling, deployment and maintenance — and where your work has a direct line to the company's top line. Responsibilities: Develop and improve ads ranking models, including prediction objectives, feature interactions, user-history modeling, and calibration Take end to end ownership of machine learning systems - from data pipelines, feature engineering, training-data construction and model evaluation, model training, as well as integration into our production systems Evaluate and apply advances in deep learning and recommendation modeling to improve ads ranking within production latency, reliability, and cost constraints Collaborate with ML platform and product engineers to build scalable and efficient machine learning systems in the production environment Partner with product, data science, and engineering teams to define ranking objectives, design A/B experiments, and measure improvements in advertiser performance, revenue, and user relevance Identify new opportunities to apply machine learning to different parts of the Ads product to drive value for our users and advertisers Minimum Requirements: Availability for meetings and impromptu communication during Quora's “ coordination hours " (Mon-Fri: 9am-3pm Pacific Time) 4+ years of professional software development experience in machine learning Hands-on experience developing and deploying ads ranking models at scale, including CTR or CVR prediction and calibration, with demonstrated ownership of production improvements Experience evaluating ranking models through offline analysis and online experiments, including investigating discrepancies between model metrics and business outcomes Experience using AI-assisted development tools for coding, testing, debugging, or data analysis, with sound judgment in validating generated code and conclusions Hands-on experience building and deploying deep learning models with PyTorch or TensorFlow Good understanding of mathematical foundations of machine learning algorithms Strong Python programming skills and experience writing maintainable production ML code. proficient coding ability writing Python BS, MS or PhD in Computer Science, Engineering or a related technical field Preferred Requirements: Experience with modern ranking architectures, such as feature interaction networks, attention-based user-sequence models, and multi-task learning Understanding of how ranking predictions and calibration interact with bidding and auctions to affect ad delivery and advertiser outcomes Experience with leading large-scale multi-engineer projects Experience addressing ranking challenges such as sparse or delayed conversion labels, sampling and exposure bias, cold-start users, or training-serving inconsistencies Experience with generative recommender systems Effective communicator with strong leadership skills 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 $189,507 - $274,604 USD + equity + benefits. Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $243,330 - $282,076 CAD + equity + benefits. For all other locations in Canada, the salary range is $227,108 - $263,271 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://www.careers.quora.com/pages/quora-global-job-applicant-privacy-notice #LI-JC1 #LI-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 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 Monetization team works on challenging problems every day. Our Machine Learning Engineers are tasked with optimizing the advertising product at Quora, and the team covers the entire Machine Learning Ads lifecycle from end-to-end, including ads targeting, ranking and auction dynamics, and quality measurement. Ingrained in our culture is the desire to constantly learn and improve, and our engineers are encouraged to think big and experiment with new ideas. Using continuous deployment, we quickly see our changes in the product and make fast iterations. As a remote-first company, our engineers have a high degree of flexibility and autonomy, and everyone on the engineering team has a huge impact on our product, revenue and company. Since we first launched our advertising platform, we've grown to support thousands of advertisers who are reaching over 300 million+ monthly unique visitors on Quora. Our journey is just beginning as we continue to build new products from the ground up and tackle exciting challenges at scale. We are looking for an experienced Machine Learning Engineer to join the Ads ML team as an ads ranking specialist. You will improve CTR and CVR prediction, model calibration, user and ad representations, and user-sequence modeling, translating improvements in ranking quality into measurable advertiser value, revenue, and better user experiences. This is a small, close-knit team where you own problems end-to-end — research, data, modeling, deployment and maintenance — and where your work has a direct line to the company's top line. Responsibilities: Develop and improve ads ranking models, including prediction objectives, feature interactions, user-history modeling, and calibration Take end to end ownership of machine learning systems - from data pipelines, feature engineering, training-data construction and model evaluation, model training, as well as integration into our production systems Evaluate and apply advances in deep learning and recommendation modeling to improve ads ranking within production latency, reliability, and cost constraints Collaborate with ML platform and product engineers to build scalable and efficient machine learning systems in the production environment Partner with product, data science, and engineering teams to define ranking objectives, design A/B experiments, and measure improvements in advertiser performance, revenue, and user relevance Identify new opportunities to apply machine learning to different parts of the Ads product to drive value for our users and advertisers Minimum Requirements: Availability for meetings and impromptu communication during Quora's “ coordination hours " (Mon-Fri: 9am-3pm Pacific Time) 4+ years of professional software development experience in machine learning Hands-on experience developing and deploying ads ranking models at scale, including CTR or CVR prediction and calibration, with demonstrated ownership of production improvements Experience evaluating ranking models through offline analysis and online experiments, including investigating discrepancies between model metrics and business outcomes Experience using AI-assisted development tools for coding, testing, debugging, or data analysis, with sound judgment in validating generated code and conclusions Hands-on experience building and deploying deep learning models with PyTorch or TensorFlow Good understanding of mathematical foundations of machine learning algorithms Strong Python programming skills and experience writing maintainable production ML code. proficient coding ability writing Python BS, MS or PhD in Computer Science, Engineering or a related technical field Preferred Requirements: Experience with modern ranking architectures, such as feature interaction networks, attention-based user-sequence models, and multi-task learning Understanding of how ranking predictions and calibration interact with bidding and auctions to affect ad delivery and advertiser outcomes Experience with leading large-scale multi-engineer projects Experience addressing ranking challenges such as sparse or delayed conversion labels, sampling and exposure bias, cold-start users, or training-serving inconsistencies Experience with generative recommender systems Effective communicator with strong leadership skills 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 $189,507 - $274,604 USD + equity + benefits. Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $243,330 - $282,076 CAD + equity + benefits. For all other locations in Canada, the salary range is $227,108 - $263,271 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://www.careers.quora.com/pages/quora-global-job-applicant-privacy-notice #LI-JC1 #LI-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 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 Monetization team works on challenging problems every day. Our Machine Learning Engineers are tasked with optimizing the advertising product at Quora, and the team covers the entire Machine Learning Ads lifecycle from end-to-end, including ads targeting, ranking and auction dynamics, and quality measurement. Ingrained in our culture is the desire to constantly learn and improve, and our engineers are encouraged to think big and experiment with new ideas. Using continuous deployment, we quickly see our changes in the product and make fast iterations. As a remote-first company, our engineers have a high degree of flexibility and autonomy, and everyone on the engineering team has a huge impact on our product, revenue and company. Since we first launched our advertising platform, we've grown to support thousands of advertisers who are reaching over 300 million+ monthly unique visitors on Quora. Our journey is just beginning as we continue to build new products from the ground up and tackle exciting challenges at scale. We are looking for an experienced Machine Learning Engineer to join the Ads ML team as an ads ranking specialist. You will improve CTR and CVR prediction, model calibration, user and ad representations, and user-sequence modeling, translating improvements in ranking quality into measurable advertiser value, revenue, and better user experiences. This is a small, close-knit team where you own problems end-to-end — research, data, modeling, deployment and maintenance — and where your work has a direct line to the company's top line. Responsibilities: Develop and improve ads ranking models, including prediction objectives, feature interactions, user-history modeling, and calibration Take end to end ownership of machine learning systems - from data pipelines, feature engineering, training-data construction and model evaluation, model training, as well as integration into our production systems Evaluate and apply advances in deep learning and recommendation modeling to improve ads ranking within production latency, reliability, and cost constraints Collaborate with ML platform and product engineers to build scalable and efficient machine learning systems in the production environment Partner with product, data science, and engineering teams to define ranking objectives, design A/B experiments, and measure improvements in advertiser performance, revenue, and user relevance Identify new opportunities to apply machine learning to different parts of the Ads product to drive value for our users and advertisers Minimum Requirements: Availability for meetings and impromptu communication during Quora's “ coordination hours " (Mon-Fri: 9am-3pm Pacific Time) 4+ years of professional software development experience in machine learning Hands-on experience developing and deploying ads ranking models at scale, including CTR or CVR prediction and calibration, with demonstrated ownership of production improvements Experience evaluating ranking models through offline analysis and online experiments, including investigating discrepancies between model metrics and business outcomes Experience using AI-assisted development tools for coding, testing, debugging, or data analysis, with sound judgment in validating generated code and conclusions Hands-on experience building and deploying deep learning models with PyTorch or TensorFlow Good understanding of mathematical foundations of machine learning algorithms Strong Python programming skills and experience writing maintainable production ML code. proficient coding ability writing Python BS, MS or PhD in Computer Science, Engineering or a related technical field Preferred Requirements: Experience with modern ranking architectures, such as feature interaction networks, attention-based user-sequence models, and multi-task learning Understanding of how ranking predictions and calibration interact with bidding and auctions to affect ad delivery and advertiser outcomes Experience with leading large-scale multi-engineer projects Experience addressing ranking challenges such as sparse or delayed conversion labels, sampling and exposure bias, cold-start users, or training-serving inconsistencies Experience with generative recommender systems Effective communicator with strong leadership skills 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 $189,507 - $274,604 USD + equity + benefits. Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $243,330 - $282,076 CAD + equity + benefits. For all other locations in Canada, the salary range is $227,108 - $263,271 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://www.careers.quora.com/pages/quora-global-job-applicant-privacy-notice #LI-JC1 #LI-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 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 Monetization team works on challenging problems every day. Our Machine Learning Engineers are tasked with optimizing the advertising product at Quora, and the team covers the entire Machine Learning Ads lifecycle from end-to-end, including ads targeting, ranking and auction dynamics, and quality measurement. Ingrained in our culture is the desire to constantly learn and improve, and our engineers are encouraged to think big and experiment with new ideas. Using continuous deployment, we quickly see our changes in the product and make fast iterations. As a remote-first company, our engineers have a high degree of flexibility and autonomy, and everyone on the engineering team has a huge impact on our product, revenue and company. Since we first launched our advertising platform, we've grown to support thousands of advertisers who are reaching over 300 million+ monthly unique visitors on Quora. Our journey is just beginning as we continue to build new products from the ground up and tackle exciting challenges at scale. We are looking for an experienced Machine Learning Engineer to join the Ads ML team as an ads ranking specialist. You will improve CTR and CVR prediction, model calibration, user and ad representations, and user-sequence modeling, translating improvements in ranking quality into measurable advertiser value, revenue, and better user experiences. This is a small, close-knit team where you own problems end-to-end — research, data, modeling, deployment and maintenance — and where your work has a direct line to the company's top line. Responsibilities: Develop and improve ads ranking models, including prediction objectives, feature interactions, user-history modeling, and calibration Take end to end ownership of machine learning systems - from data pipelines, feature engineering, training-data construction and model evaluation, model training, as well as integration into our production systems Evaluate and apply advances in deep learning and recommendation modeling to improve ads ranking within production latency, reliability, and cost constraints Collaborate with ML platform and product engineers to build scalable and efficient machine learning systems in the production environment Partner with product, data science, and engineering teams to define ranking objectives, design A/B experiments, and measure improvements in advertiser performance, revenue, and user relevance Identify new opportunities to apply machine learning to different parts of the Ads product to drive value for our users and advertisers Minimum Requirements: Availability for meetings and impromptu communication during Quora's “ coordination hours " (Mon-Fri: 9am-3pm Pacific Time) 4+ years of professional software development experience in machine learning Hands-on experience developing and deploying ads ranking models at scale, including CTR or CVR prediction and calibration, with demonstrated ownership of production improvements Experience evaluating ranking models through offline analysis and online experiments, including investigating discrepancies between model metrics and business outcomes Experience using AI-assisted development tools for coding, testing, debugging, or data analysis, with sound judgment in validating generated code and conclusions Hands-on experience building and deploying deep learning models with PyTorch or TensorFlow Good understanding of mathematical foundations of machine learning algorithms Strong Python programming skills and experience writing maintainable production ML code. proficient coding ability writing Python BS, MS or PhD in Computer Science, Engineering or a related technical field Preferred Requirements: Experience with modern ranking architectures, such as feature interaction networks, attention-based user-sequence models, and multi-task learning Understanding of how ranking predictions and calibration interact with bidding and auctions to affect ad delivery and advertiser outcomes Experience with leading large-scale multi-engineer projects Experience addressing ranking challenges such as sparse or delayed conversion labels, sampling and exposure bias, cold-start users, or training-serving inconsistencies Experience with generative recommender systems Effective communicator with strong leadership skills 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 $189,507 - $274,604 USD + equity + benefits. Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $243,330 - $282,076 CAD + equity + benefits. For all other locations in Canada, the salary range is $227,108 - $263,271 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://www.careers.quora.com/pages/quora-global-job-applicant-privacy-notice #LI-JC1 #LI-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 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 Monetization team works on challenging problems every day. Our Machine Learning Engineers are tasked with optimizing the advertising product at Quora, and the team covers the entire Machine Learning Ads lifecycle from end-to-end, including ads targeting, ranking and auction dynamics, and quality measurement. Ingrained in our culture is the desire to constantly learn and improve, and our engineers are encouraged to think big and experiment with new ideas. Using continuous deployment, we quickly see our changes in the product and make fast iterations. As a remote-first company, our engineers have a high degree of flexibility and autonomy, and everyone on the engineering team has a huge impact on our product, revenue and company. Since we first launched our advertising platform, we've grown to support thousands of advertisers who are reaching over 300 million+ monthly unique visitors on Quora. Our journey is just beginning as we continue to build new products from the ground up and tackle exciting challenges at scale. We are looking for an experienced Machine Learning Engineer to join the Ads ML team as an ads ranking specialist. You will improve CTR and CVR prediction, model calibration, user and ad representations, and user-sequence modeling, translating improvements in ranking quality into measurable advertiser value, revenue, and better user experiences. This is a small, close-knit team where you own problems end-to-end — research, data, modeling, deployment and maintenance — and where your work has a direct line to the company's top line. Responsibilities: Develop and improve ads ranking models, including prediction objectives, feature interactions, user-history modeling, and calibration Take end to end ownership of machine learning systems - from data pipelines, feature engineering, training-data construction and model evaluation, model training, as well as integration into our production systems Evaluate and apply advances in deep learning and recommendation modeling to improve ads ranking within production latency, reliability, and cost constraints Collaborate with ML platform and product engineers to build scalable and efficient machine learning systems in the production environment Partner with product, data science, and engineering teams to define ranking objectives, design A/B experiments, and measure improvements in advertiser performance, revenue, and user relevance Identify new opportunities to apply machine learning to different parts of the Ads product to drive value for our users and advertisers Minimum Requirements: Availability for meetings and impromptu communication during Quora's “ coordination hours " (Mon-Fri: 9am-3pm Pacific Time) 4+ years of professional software development experience in machine learning Hands-on experience developing and deploying ads ranking models at scale, including CTR or CVR prediction and calibration, with demonstrated ownership of production improvements Experience evaluating ranking models through offline analysis and online experiments, including investigating discrepancies between model metrics and business outcomes Experience using AI-assisted development tools for coding, testing, debugging, or data analysis, with sound judgment in validating generated code and conclusions Hands-on experience building and deploying deep learning models with PyTorch or TensorFlow Good understanding of mathematical foundations of machine learning algorithms Strong Python programming skills and experience writing maintainable production ML code. proficient coding ability writing Python BS, MS or PhD in Computer Science, Engineering or a related technical field Preferred Requirements: Experience with modern ranking architectures, such as feature interaction networks, attention-based user-sequence models, and multi-task learning Understanding of how ranking predictions and calibration interact with bidding and auctions to affect ad delivery and advertiser outcomes Experience with leading large-scale multi-engineer projects Experience addressing ranking challenges such as sparse or delayed conversion labels, sampling and exposure bias, cold-start users, or training-serving inconsistencies Experience with generative recommender systems Effective communicator with strong leadership skills 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 $189,507 - $274,604 USD + equity + benefits. Canada candidates only: For Toronto and Vancouver based applicants, the salary range is $243,330 - $282,076 CAD + equity + benefits. For all other locations in Canada, the salary range is $227,108 - $263,271 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://www.careers.quora.com/pages/quora-global-job-applicant-privacy-notice #LI-JC1 #LI-REMOTE