Software Engineer, Machine Learning Platform, New Grad - Quora (Remote)

Quora

11d • $97,600 - $139,000 • Remote

About The Position

This role is for a Software Engineer (New Grad) on Quora's Machine Learning Platform team. The team owns Quora's ML platform and ranking infrastructure, focusing on serving reliability, ML engineer enablement and developer velocity, business impact, and cost efficiency. The goal is to empower ML engineers to solve ML problems at scale. The role involves working at the intersection of Machine Learning, Distributed Systems, and GPU Serving performance. No prior ML infrastructure experience is required, as new hires will receive mentorship and technical guidance, with the expectation of shipping to production within their first few weeks. The position can be performed remotely from anywhere in Canada or the United States.

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

Nice To Haves

• 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

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 (LRM) to Large Language Models (LLM)
• 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

Benefits

• medical/dental/vision coverage
• equity refreshers
• remote work reimbursement
• paid time off
• employee assistance programs

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: High school or GED