Machine Learning Engineer II developing production ML models for Affirm’s pay - over - time platform. Building credit decisioning systems, scalable pipelines, and algorithms that predict default and guide approvals.
About the role
- New-grad Machine Learning Engineer building LLM agents and moderation systems for Quora’s knowledge-sharing platform. Evaluating and deploying ML solutions that improve content quality and safety at scale.
Responsibilities
- Design, build, and deploy LLM-powered agents to detect and address spam, harassment, and other policy-violating content at Quora's scale
- Develop agentic workflows to automate complex tasks and improve 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, balancing accuracy, reliability, latency, and cost
- Investigate failure cases, experiment with new approaches, and iterate on solutions to improve system performance
- Identify opportunities to apply ML and LLMs to content quality and safety across Quora
- Collaborate with experienced engineers and own projects from early development through production
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
- Able to start full-time in early 2027
- Previous software engineering experience via an internship, work experience, open-source contribution, or coding competition (preferred)
- Hands-on experience building and evaluating LLM agents (preferred)
- Regular use of AI coding tools such as Claude Code or Codex (preferred)
- Coursework or projects in natural language processing (NLP) (preferred)
- Genuine interest in content safety and quality (preferred)
- Passion for Quora's mission and goals (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 any sponsorship requirement
Benefits
- Medical, dental, and vision coverage
- Equity refreshers
- Remote work reimbursement
- Paid time off
- Employee assistance programs
- Flexible equity program allowing a portion of equity compensation to be taken as cash in equity-eligible countries
- Equity and benefits
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