Machine Learning Engineer - Ads Ranking Specialist (Remote)

Quora’s mission is to grow the world's collective intelligence. Behind its products—Quora, a global knowledge-sharing platform with millions of monthly unique visitors, and Poe, an AI-powered chat and exploration platform—are passionate, collaborative, and high-performing global teams. This role will focus on the Quora product.

About the Team and Role:

The Monetization team tackles challenging problems daily. Machine Learning Engineers optimize Quora’s advertising product, covering the entire Machine Learning Ads lifecycle—ads targeting, ranking, auction dynamics, and quality measurement. The team thrives on learning, experimentation, and innovation, with engineers deploying changes rapidly via continuous deployment. As a remote-first company, engineers enjoy flexibility, autonomy, and direct impact on product, revenue, and company growth.

Since launching its advertising platform, Quora now supports thousands of advertisers reaching over 300 million+ monthly unique visitors. The team is expanding with new products and scaling solutions. Quora seeks an experienced Machine Learning Engineer to join the Ads ML team as an ads ranking specialist. The role involves improving CTR and CVR prediction, model calibration, user and ad representations, and user-sequence modeling. Improvements directly translate to advertiser value, revenue growth, and better user experiences. This is a small, close-knit team where ownership spans research, data, modeling, deployment, and maintenance—with a direct line to the company’s top line.

Responsibilities:

• Develop and refine ads ranking models, including prediction objectives, feature interactions, user-history modeling, and calibration.
• Take end-to-end ownership of machine learning systems—data pipelines, feature engineering, training-data construction, model evaluation, training, and production integration.
• Evaluate and apply advances in deep learning and recommendation modeling while adhering to production constraints for latency, reliability, and cost.
• Collaborate with ML platform and product engineers to build scalable, efficient machine learning systems.
• 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 opportunities to apply machine learning to other parts of the Ads product to drive value for users and advertisers.

Minimum 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.
• Strong understanding of the mathematical foundations of machine learning algorithms.
• Proficient Python programming skills and experience writing maintainable production ML code.
• BS, MS, or PhD in Computer Science, Engineering, or a related technical field.

Preferred Requirements:

• 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 leading large-scale multi-engineer projects.
• Experience addressing ranking challenges like 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.

At Quora, diversity and inclusivity are valued. Individuals from all backgrounds, including marginalized or underrepresented groups in tech, are encouraged to apply, even if they don’t strictly meet all requirements.