Senior Machine Learning Engineer, Ads - Quora (Remote)

Quora
•$189,507 - $274,604•Remote

About The Position

Quora is a remote-first company with a mission to grow the world's collective intelligence through its knowledge sharing platform, Quora, and its AI chatbot platform, Poe. This role is focused on the Quora product, specifically within the Monetization team. The team optimizes the advertising product by working on ads targeting, ranking, auction dynamics, and quality measurement. They utilize continuous deployment for rapid iteration and offer engineers significant flexibility, autonomy, and impact in a remote-first environment. The advertising platform supports thousands of advertisers and reaches over 300 million monthly unique visitors. The company is looking for an experienced Machine Learning Engineer to specialize in ads ranking, aiming to improve CTR and CVR prediction, model calibration, user and ad representations, and user-sequence modeling to enhance advertiser value, revenue, and user experience. This is a small, close-knit team where the engineer will own problems end-to-end, from research to maintenance, with a direct impact on the company's revenue.

Requirements

  • Availability for meetings and impromptu communication during Quora's “coordination hours" (Mon-Fri: 9am-3pm Pacific Time)
  • 4+ years of professional software development experience in machine learning
  • Hands-on experience developing and deploying ads ranking models at scale, including CTR or CVR prediction and calibration, with demonstrated ownership of production improvements
  • Experience evaluating ranking models through offline analysis and online experiments, including investigating discrepancies between model metrics and business outcomes
  • Experience using AI-assisted development tools for coding, testing, debugging, or data analysis, with sound judgment in validating generated code and conclusions
  • Hands-on experience building and deploying deep learning models with PyTorch or TensorFlow
  • Good understanding of mathematical foundations of machine learning algorithms
  • Strong Python programming skills and experience writing maintainable production ML code. proficient coding ability writing Python
  • BS, MS or PhD in Computer Science, Engineering or a related technical field

Nice To Haves

  • Experience with modern ranking architectures, such as feature interaction networks, attention-based user-sequence models, and multi-task learning
  • Understanding of how ranking predictions and calibration interact with bidding and auctions to affect ad delivery and advertiser outcomes
  • Experience with leading large-scale multi-engineer projects
  • Experience addressing ranking challenges such as sparse or delayed conversion labels, sampling and exposure bias, cold-start users, or training-serving inconsistencies
  • Experience with generative recommender systems
  • Effective communicator with strong leadership skills
  • Passion for Quora's mission and goals

Responsibilities

  • Develop and improve ads ranking models, including prediction objectives, feature interactions, user-history modeling, and calibration
  • Take end to end ownership of machine learning systems - from data pipelines, feature engineering, training-data construction and model evaluation, model training, as well as integration into our production systems
  • Evaluate and apply advances in deep learning and recommendation modeling to improve ads ranking within production latency, reliability, and cost constraints
  • Collaborate with ML platform and product engineers to build scalable and efficient machine learning systems in the production environment
  • Partner with product, data science, and engineering teams to define ranking objectives, design A/B experiments, and measure improvements in advertiser performance, revenue, and user relevance
  • Identify new opportunities to apply machine learning to different parts of the Ads product to drive value for our users and advertisers

Benefits

  • medical/dental/vision coverage
  • equity refreshers
  • remote work reimbursement
  • paid time off
  • employee assistance programs
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