Quora

240 Total Employees
Year Founded: 2009

Jobs at Quora

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Recently posted jobs

10 Days AgoSaved
In-Office or Remote
4 Locations
Artificial Intelligence • Consumer Web • Digital Media • Machine Learning • Software
Lead the technical direction of Quora’s recommendation ecosystem, including feed retrieval, ranking, re-ranking, optimization, data pipelines, feature engineering, model training, and production integration. Drive measurable improvements through experimentation, apply generative AI, mentor engineers, and partner across product, data science, and infrastructure teams.
20 Days AgoSaved
In-Office or Remote
4 Locations
Artificial Intelligence • Consumer Web • Digital Media • Machine Learning • Software
Lead growth initiatives for Quora’s core web and mobile products, owning acquisition, activation, and early retention. Partner with engineering, design, data science, and product operations to define objectives, build experiences, run experiments, analyze user insights, and identify strategic growth opportunities. The role requires influencing cross-functional teams, expanding reach to new demographics, and driving measurable user growth through qualitative and quantitative research.
24 Days AgoSaved
In-Office or Remote
4 Locations
Artificial Intelligence • Consumer Web • Digital Media • Machine Learning • Software
Own and improve Quora’s second-phase ranking models for feed and digest experiences. Build end-to-end machine learning systems covering data pipelines, candidate extraction, feature engineering, model training, and production integration. Identify new product applications for machine learning, develop efficient algorithms with other ML engineers, and contribute methodologies for large-scale recommendation systems.
One Month AgoSaved
In-Office or Remote
4 Locations
Artificial Intelligence • Consumer Web • Digital Media • Machine Learning • Software
Develop and optimize large-scale advertising ranking models for CTR and CVR prediction, calibration, user representations, and sequence modeling. Own machine learning systems end to end, including data pipelines, feature engineering, training, evaluation, deployment, and maintenance. Collaborate with platform, product, data science, and engineering teams to run experiments and improve advertiser outcomes, revenue, and user relevance. Apply deep learning and recommendation techniques within production latency, reliability, and cost constraints.