Staff Machine Learning Engineer, Recommendation Systems

At Quora, machine learning drives nearly every aspect of our product, and our lean, high-velocity engineering team tackles complex, high-impact challenges daily. We thrive in a remote-first culture built on absolute autonomy, continuous learning, and bold experimentation.

We are looking for a Staff Machine Learning Engineer to define the technical future of Quora’s recommendation ecosystem. In this role, you will own the technical direction for feed ranking and retrieval, lead our highest-impact modeling bets, and pioneer the integration of LLMs and generative models to redefine how we understand and rank content. Beyond the home feed, you will also scale recommendation surfaces like notifications and digest emails, while architecting the underlying tools and abstractions that empower our entire engineering organization.

This is a high-leverage, hands-on IC role with organization-wide scope. You will write production code, mentor rising talent, and actively shape how our team leverages AI-assisted development to accelerate our shipping velocity.

- Set the technical direction for Quora’s home feed recommendation systems

- Lead the highest-impact projects across the recommender stack, from candidate generation and retrieval to ranking, re-ranking, and multi-objective optimization

- Drive measurable improvements in user engagement and content quality through well-designed online experiments

- Take end-to-end ownership of ML systems, including data pipelines, candidate extraction, feature engineering, model training, and production integration

- Identify new opportunities to apply machine learning to different parts of the Quora product

- Partner with product, data science, and infrastructure teams to align on priorities and tradeoffs

- Mentor engineers and lead by example, raising the bar for code quality, modeling rigor and AI assisted dev velocity

- Availability for meetings and impromptu communication during Quora's “coordination hours https://quora.com/coordination_hours" (Mon-Fri: 9am-3pm Pacific Time)