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Tech Stack
Tools & technologiesAWSDistributed SystemsDockerKubernetesPythonPyTorchTensorflowC++Go
About the role
Key responsibilities & impact- Build and maintain core infrastructure powering Quora's machine learning platform
- Ensure high availability, scalability, and performance of ML platform infrastructure
- Build and improve distributed systems serving production ML models, including LRMs and LLMs
- Work on GPU model serving and optimize latency, throughput, and cost
- Contribute to PyTorch-first standardization and ML ecosystem modernization
- Build tooling that improves ML engineers' development, testing, and deployment velocity
- Modernize the feature store to accelerate productionization of new features
- Participate in the on-call rotation and help resolve production issues
- Ship production work within the first few weeks while learning from senior and staff engineers
Requirements
What you’ll need- Availability for meetings and impromptu communication during Quora's coordination hours, Monday–Friday, 9am–3pm Pacific Time
- 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 ability to learn them quickly
- Previous software engineering experience through an internship, work experience, open-source contribution, or coding competition preferred
- Coursework or hands-on experience with PyTorch or TensorFlow preferred
- Exposure to Kubernetes, Docker, or AWS preferred
- Experience with profiling, benchmarking, or optimization preferred
- Final candidates must undergo identity verification and a comprehensive background check prior to onboarding
- Candidates must be legally authorized to work in the selected employment-eligible country and disclose whether visa sponsorship is required
Benefits
Comp & perks- Medical, dental, and vision coverage
- Equity refreshers
- Remote work reimbursement
- Paid time off
- Employee assistance programs
- Flexible equity program in equity-eligible countries, allowing a portion of equity compensation to be taken as cash
- Dedicated mentor and strong technical guidance
- Remote-first work arrangement