501-1000 employees
The Staff Machine Learning Engineer will define the technical direction for Quora's home feed recommendation systems and lead high-impact projects across the recommender stack. They will also mentor engineers, write production code, and partner with cross-functional teams to integrate generative models and improve user engagement.
Develop full stack applications using Python and React to enhance the core Quora product experience. Collaborate with cross-functional teams to design and launch features at scale while utilizing data and experimentation to guide iterations.
Partner with engineering teams to assess cloud and compute architecture, create threat models, and develop security policies and controls. Build automation and security tooling for infrastructure hardening, logging, threat detection, incident containment, network access management, and incident response.
Design, build, and deploy LLM-powered agents to detect and address policy-violating content at scale. Develop agentic workflows to automate complex tasks and improve the efficiency of content moderation systems.
The Lead Product Manager will own the end-to-end user growth funnel, focusing on acquisition, activation, and retention across web and mobile platforms. They will partner with engineering, design, and data science teams to run high-velocity experiments and drive long-term platform strategy.
You will own and advance the second-phase ranking models for Quora's feed and digest surfaces using advanced machine learning techniques. Additionally, you will take end-to-end ownership of machine learning systems, including data pipelines, feature engineering, and production integration.
The role involves building and maintaining the core infrastructure for Quora's machine learning platform to ensure high availability and scalability. You will also optimize GPU model serving and improve developer velocity by creating efficient tooling for ML engineers.
Develop and optimize ads ranking models, including CTR/CVR prediction and user-history modeling, while taking end-to-end ownership of machine learning systems. Collaborate with cross-functional teams to define ranking objectives, design experiments, and integrate scalable solutions into production.
Build and maintain SIEM infrastructure to detect and alert on malicious behavior across corporate and production environments. Manage corporate security controls, endpoint protection, and Zero-Trust VPN implementation while providing security advisory to non-technical teams.
