Requirements

Availability for meetings and impromptu communication during Quora's coordination hours (Mon-Fri: 9am-3pm Pacific Time)
B.S., M.S., or Ph.D. in Computer Science, Engineering or a related technical field, completed or in progress
Strong understanding of mathematical foundations of Machine Learning algorithms
Coursework, research, or project experience with LLM applications or transformer models
Strong knowledge of Python
A passion for learning and continuous self-improvement
Able to start full-time in early 2027

Nice to Haves

Previous software engineering experience via internship, work experience, open-source contribution or coding competition
Hands-on experience building and evaluating LLM agents in projects, research, internships, or production
Regular use of AI coding tools such as Claude Code or Codex
Coursework or projects in natural language processing (NLP)
Genuine interest in content safety and quality
Passion for Quora's mission and goals

Design, build, and deploy LLM-powered agents to detect and address spam, harassment, and other policy-violating content at scale
Develop agentic workflows to automate complex tasks for content and user moderation systems
Design and improve ML systems that adapt to evolving abuse patterns and new challenges
Evaluate agent performance through offline evaluations, online experiments, and production monitoring focusing on accuracy, reliability, latency, and cost
Investigate failure cases, experiment with new approaches, and iterate to improve system performance
Identify new opportunities to apply ML and LLMs to content quality and safety
Collaborate with experienced engineers and take ownership of projects from development through production

Medical, dental, and vision coverage
Equity refreshers and a flexible equity program with option for cash in eligible countries
Remote work reimbursement
Paid time off and employee assistance programs
Competitive salary ranges based on location and experience (US: $107,360 - $152,900 USD; Canada varies by city)
Inclusive and diverse work environment valuing multiple perspectives