Senior Machine Learning Engineer, Ads

Stellenbeschreibung:

• Develop and improve ads ranking models, including prediction objectives, feature interactions, user-history modeling, and calibration
• Own machine learning systems end-to-end, including data pipelines, feature engineering, training-data construction, model evaluation, model training, and production integration
• Evaluate and apply advances in deep learning and recommendation modeling within production latency, reliability, and cost constraints
• Collaborate with ML platform and product engineers to build scalable and efficient production machine learning systems
• Partner with product, data science, and engineering teams to define ranking objectives, design A/B experiments, and measure advertiser performance, revenue, and user relevance
• Identify opportunities to apply machine learning across the Ads product
• Improve CTR and CVR prediction, model calibration, user and ad representations, and user-sequence modeling
• Translate ranking-quality improvements into advertiser value, revenue, and better user experiences

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
Demonstrated ownership of production improvements
Experience evaluating ranking models through offline analysis and online experiments
Experience investigating discrepancies between model metrics and business outcomes
Experience using AI-assisted development tools for coding, testing, debugging, or data analysis
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
Experience writing maintainable production ML code
BS, MS or PhD in Computer Science, Engineering or a related technical field
Preferred: experience with modern ranking architectures, feature interaction networks, attention‑based user‑sequence models, and multi‑task learning
Preferred: understanding of ranking predictions and calibration with bidding and auctions
Preferred: experience with large‑scale multi‑engineer projects
Preferred: experience addressing sparse or delayed conversion labels, sampling and exposure bias, cold‑start users, and training‑serving inconsistencies
Preferred: experience with generative recommender systems

Core Competencies

Demonstrates expertise in developing and deploying machine learning models, particularly in ads ranking, with a strong focus on improving CTR and CVR predictions. Proficient in collaborating with cross‑functional teams to enhance model performance and translate technical improvements into business value.