New Grad ML Platform Engineer

Quora; United States; On-site; USD 110,000 - 150,000; Full time

Job summary

Quora is seeking a Software Engineer (New Grad) to join the ML platform team, combining machine learning, distributed systems, and GPU serving performance. You'll join a team of senior engineers with mentorship and ship to production in weeks.

You will build core infrastructure powering Quora's ML models at scale, improve developer velocity, and modernize feature stores while learning through hands-on experience with PyTorch, Kubernetes, and cloud tech.

Qualifications

• No prior ML infrastructure experience required.
• Knowledge of Python, Go, or C++, or ability to learn them quickly.
• Passion for learning and improving yourself and the team.
• 2025 or 2026 graduate with a degree in CS/Engineering or related field.
• Experience via internship, work, open-source, or coding competition.
• Exposure to Kubernetes, Docker, or cloud technologies like AWS.
• Coursework or hands-on experience with ML frameworks such as PyTorch or TensorFlow.
• Experience with low-level performance work: profiling, benchmarking, optimization.

Responsibilities

• Build and maintain the core infrastructure powering Quora's ML platform.
• Develop distributed systems to serve ML models in production, from LRMs to LLMs.
• Work on GPU model serving to optimize latency, throughput, and cost.
• Contribute to platform initiatives like PyTorch-first standardization and ML ecosystem modernization.

Skills

Python

Go

C++

PyTorch

Kubernetes/EKS

Ray

NVIDIA Triton

AWS

Education

BS/MS/PhD in Computer Science or related technical field

Tools

Kubernetes

Docker

AWS

Job description

Quora is seeking a Software Engineer (New Grad) to join the ML platform team, combining machine learning, distributed systems, and GPU serving performance. You'll join a team of senior engineers with mentorship and ship to production in weeks.

You will build core infrastructure powering Quora's ML models at scale, improve developer velocity, and modernize feature stores while learning through hands-on experience with PyTorch, Kubernetes, and cloud tech.