Machine Learning Engineer, New Grad - Quora (remote)

Quora Quora · Consumer · Multiple · Remote · Engineering

Machine Learning Engineer role focused on building and improving consumer-facing AI systems for Quora's product, utilizing LLMs and generative AI. Responsibilities include model development, experimentation, productionization, prompt engineering, agentic workflow optimization, evaluation, and optimizing AI systems for latency and cost. This is a new grad role.

What you'd actually do

  1. Build and iterate on consumer-facing AI features powered by large language models (LLMs) and related generative AI systems
  2. Collaborate with engineers across the AI engineering stack — prompt engineering, agentic workflow optimization, evaluation and more
  3. Run structured experiments (e.g., A/B tests, offline evaluations) to measure impact on engagement, quality, and trust metrics
  4. Partner closely with product and engineering to translate user needs into scalable AI-powered solutions
  5. Strengthen model reliability through monitoring, guardrails, quality analysis, and failure mode investigation
  6. Optimize the latency, cost, and scalability of production AI systems

Skills

Required

  • Availability for meetings and impromptu communication during Quora's “coordination hours" (Mon-Fri: 9am-3pm Pacific Time)
  • A 2024, 2025 or 2026 graduate with or pursuing a B.S., M.S., or Ph.D. in Computer Science, Engineering or a related technical field
  • Strong understanding of mathematical foundations of Machine Learning algorithms
  • Experience of LLM applications or transformer models
  • Knowledge of Python or C++, or the ability to learn them quickly
  • Strong command of written English, with the ability to evaluate tone, accuracy, clarity, and nuance in written content

Nice to have

  • Previous software engineering experience via an internship, work experience or coding competition
  • Hands-on experience building agents in a production environment at scale
  • Passion for Quora's mission and goals

What the JD emphasized

  • consumer-facing AI features
  • LLMs
  • generative AI systems
  • productionization
  • agentic workflow optimization
  • evaluation
  • latency
  • cost
  • scalability

Other signals

  • consumer-facing AI features
  • LLM applications
  • generative AI systems
  • productionization