Senior Machine Learning Engineer, Ads - Quora

Quora is a privately held, remote-first company. This position can be performed remotely from multiple countries around the world.

About Quora

Quora's mission is to grow the world's collective intelligence. To do so, we have two platforms:

• Quora: A global knowledge sharing platform with millions of monthly unique visitors, bringing people together to share insights on various topics and providing a unique platform to learn and connect with others.
• Poe: A platform providing millions of global users with one place to chat, explore, and build with a wide variety of AI language models.

Behind these products are passionate, collaborative, and high-performing global teams. Join us on this journey to create a positive impact and make a significant change in the world.

This role will be working on our Quora product.

About the Team and Role

Our Monetization team works on challenging problems every day. Our Machine Learning Engineers are tasked with optimizing the advertising product at Quora, covering the entire Machine Learning Ads lifecycle end-to-end, including ads targeting, ranking, auction dynamics, and quality measurement.

We are looking for an experienced Machine Learning Engineer to join the Ads ML team as an ads ranking specialist. You will improve CTR and CVR prediction, model calibration, user and ad representations, and user-sequence modeling, translating improvements in ranking quality into measurable advertiser value, revenue, and better user experiences.

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 to model training and integration into 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 production.
• 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 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.
• Good understanding of the mathematical foundations of machine learning algorithms.
• Strong 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 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.

Benefits & Compensation

• US base salary range: $189,507 - $274,604 USD + equity + benefits.
• Canada base salary range: $243,330 - $282,076 CAD (Toronto/Vancouver) or $227,108 - $263,271 CAD (other Canada locations) + equity + benefits.
• Medical, dental, and vision coverage.
• Equity refreshers.
• Remote work reimbursement.
• Paid time off and employee assistance programs.