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

Quora Quora · Consumer · Multiple · Remote · Engineering

Software Engineer (New Grad) on the ML Platform team at Quora, focusing on building and maintaining the core infrastructure for ML models, including GPU serving performance, ML developer enablement, and feature store modernization. The role involves working with distributed systems and optimizing inference for both recommendation and language models.

What you'd actually do

  1. Help build and maintain the core infrastructure that powers Quora's ML platform, ensuring high availability, scalability, and performance
  2. Build and improve the distributed systems that serve our ML models in production, from Large Recommendation Models (LRM) to Large Language Models (LLM)
  3. Work on GPU model serving, optimizing latency, throughput, and cost to support larger and more capable models
  4. Contribute to platform initiatives such as PyTorch-first standardization and ML ecosystem modernization
  5. Improve ML developer velocity by building tooling that helps ML engineers develop, test, and deploy models more efficiently

Skills

Required

  • 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 have

  • 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

Other signals

  • ML platform
  • serving infrastructure
  • GPU serving performance
  • ML developer velocity
  • feature store