[All remote jobs](https://jobicy.com/jobs.md)[![Quora logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2020/09/WRILS-200916172339-629302.jpg)](https://jobicy.com/company/quora.md)[Quora](https://jobicy.com/company/quora.md) # Software Engineer New Grad, Machine Learning Platform – Quora Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/quora.md)ShareRemote from[UK](https://jobicy.com/job-region/uk.md), [USA](https://jobicy.com/job-region/usa.md), [Canada](https://jobicy.com/job-region/canada.md)SalaryUSD 97,600–139k / yrDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceSeniorPublished30 Sep 2026Apply before30 Oct 2026Listing views37Application actions1Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. Quora is hiring a new-graduate Software Engineer to build and operate its machine learning platform and ranking infrastructure. The role focuses on distributed systems, reliable model serving, GPU performance optimization, developer tooling, and feature-store modernization. Engineers will work with Python, Go, C++, PyTorch, Kubernetes/EKS, NVIDIA Triton, Ray, and AWS while receiving dedicated mentorship from senior engineers. The position includes production ownership, on-call participation as knowledge grows, and collaboration during Pacific Time coordination hours. It is remote-first and open to candidates located in the United States or Canada. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 4/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 3/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is an early-career role with structured mentorship, but the technical environment is demanding because it involves production ML infrastructure, distributed systems, GPU serving, and high-scale reliability. Candidates must learn quickly and contribute production-quality work soon after joining. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianMarket rate$118,300US market range$95k–$145k0$160k AI insightThe disclosed US annual salary range is $97,600 to $139,000 USD, with a midpoint of $118,300 USD. This aligns with an estimated US market range of $95,000 to $145,000 USD annually for a new-graduate software engineer focused on infrastructure and machine-learning platforms. The posting also discloses separate Canadian annual salary ranges in CAD: $125,320–$142,783 for Toronto/Vancouver and $116,965–$133,264 for other Canadian locations. ## Core skills Skills and capabilities most closely associated with this opportunity. [Python](https://jobicy.com/jobs?search_keywords=Python.md)[Go](https://jobicy.com/jobs?search_keywords=Go.md)[C++](https://jobicy.com/jobs?search_keywords=C%2B%2B.md)[Machine Learning Infrastructure](https://jobicy.com/jobs?search_keywords=Machine%20Learning%20Infrastructure.md)[Distributed Systems](https://jobicy.com/jobs?search_keywords=Distributed%20Systems.md)[GPU Serving](https://jobicy.com/jobs?search_keywords=GPU%20Serving.md)[PyTorch](https://jobicy.com/jobs?search_keywords=PyTorch.md)[Kubernetes](https://jobicy.com/jobs?search_keywords=Kubernetes.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[Performance Optimization](https://jobicy.com/jobs?search_keywords=Performance%20Optimization.md) Sample interview questionsHow would you approach diagnosing high latency in a production model-serving system?I would first define the affected request path and inspect service-level metrics such as p50/p95/p99 latency, error rate, throughput, GPU utilization, queue depth, and resource saturation. I would use tracing and profiling to isolate whether the bottleneck is request queuing, preprocessing, network calls, model inference, batching, or postprocessing, then validate improvements through controlled load tests. What trade-offs would you consider when batching inference requests on GPUs? Batching can improve GPU utilization and throughput by amortizing overhead across requests, but larger batches can increase queueing delay and harm tail latency. I would tune batch size and batching timeout using production traffic patterns, model characteristics, latency SLOs, and available GPU memory. Describe how you would make a distributed service more reliable. I would begin with clear SLOs and observable metrics, then add health checks, timeouts, retries with backoff, circuit breakers, load shedding, and graceful degradation where appropriate. I would also ensure safe deployments, capacity planning, fault testing, documented runbooks, and post-incident learning to address recurring failure modes. How would you evaluate whether a performance optimization is worthwhile? I would establish a baseline with representative benchmarks and production metrics, identify the limiting resource, and make one measurable change at a time. An optimization is worthwhile if it provides meaningful improvements in latency, throughput, reliability, or cost without creating unacceptable complexity, regressions, or operational risk. What would you do when asked to work with an unfamiliar technology such as Triton or Ray? I would clarify the problem and success criteria, study the system documentation and existing internal examples, build a small test implementation, and ask focused questions from teammates or my mentor. I would validate my understanding with tests and monitoring, document what I learned, and incrementally expand the change rather than making broad unverified modifications. Opportunity details ## About this role. [[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://www.careers.quora.com/pages/quora-global-job-applicant-privacy-notice](https://www.careers.quora.com/pages/quora-global-job-applicant-privacy-notice) #LI-SS2 #LI-REMOTE Show more [Apply now >](https://jobicy.com/jobs/154244-software-engineer-new-grad-machine-learning-platform-quora.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. 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