New-grad software engineer building Quora’s distributed ML platform, model serving, and developer tooling. Supporting Quora’s global knowledge-sharing product with scalable GPU infrastructure.
Responsibilities
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
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
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
Director leading agentic AI and machine learning products for Instacart’s grocery technology platform. Building retailer solutions and guiding teams from strategy through production deployment.
Applied Machine Learning Scientist developing Generative AI and predictive ML solutions at TD, a major North American bank. Supporting model evaluation, deployment, monitoring, and responsible AI governance.
Applied Machine Learning Scientist developing Generative AI and predictive ML solutions for TD banking. Evaluating models, managing AI lifecycles, and supporting responsible implementation.
Senior Machine Learning Engineer building conversational AI agents and production ML systems. Helping Numa automate automotive dealership service and sales through evaluation - first tooling and infrastructure.
Senior ML Engineer building production ML, RAG, and agentic AI capabilities for SailPoint’s cloud identity security platform. Driving scalable, customer - focused AI solutions from research to production.
Senior ML Engineer developing debiased pCTR and conversion models for Instacart’s grocery advertising ecosystem. Advancing ranking, retrieval, and sequence modeling across ads surfaces.
Senior AI/ML Engineer building Generative AI, RAG, and agentic solutions for pharmaceutical Statistical Programming. Deploying secure, validated, production - ready AI applications with Python and AWS.
Senior Machine Learning Engineer building LLM - powered lab interpretation and clinical decision - support tools for Fullscript’s healthcare platform. Owning AI systems from prototyping through production.
Staff ML engineer building models, evaluations, and agentic systems for Sourcegraph’s code - understanding products. Improving enterprise code search quality, latency, cost, and reliability.