Senior Machine Learning Engineer, Ads

Jobtailor; Deutschland; Remote; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

Jobtailor is seeking an experienced ML Engineer to develop and deploy ads ranking models at scale, focusing on CTR/CVR prediction and calibration. You will own end-to-end ML systems, from data pipelines to production integration, and collaborate across product and engineering teams to drive advertiser value.

The role emphasizes building scalable, reliable ML systems, evaluating models with offline analyses and online experiments, and leveraging deep learning techniques within production

Qualifikationen

• 4+ years of professional software development experience in machine learning.
• Hands-on experience developing and deploying ads ranking models at scale.
• Experience with PyTorch or TensorFlow in production.
• BS/MS/PhD in CS/Engineering or related field.
• Experience with offline and online ranking model evaluation.

Aufgaben

• Develop and improve ads ranking models end-to-end, 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.
• Collaborate with ML platform and product engineers to build scalable and efficient production ML 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/ad representations, and user-sequence modeling.

Kenntnisse

Machine Learning Systems Ownership

Ads Ranking Model Development

Deep Learning (PyTorch/TF)

Python Programming

Model Evaluation & A/B Testing

Data Pipelines

CTR Prediction

CVR Prediction

Feature Engineering

Production ML Code

Ausbildung

BS in Computer Science

MS in Engineering

PhD in Related Technical Field

Tools

PyTorch

TensorFlow

AI-Assisted Development Tools

Jobbeschreibung

• 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.

Highest-signal resume keywords

• Machine Learning Systems Ownership
• Ads Ranking Model Development
• Deep Learning with PyTorch or TensorFlow
• Python Programming
• Model Evaluation and A/B Testing

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Ads Ranking Models
• CTR Prediction
• CVR Prediction
• Model Calibration
• Feature Engineering
• Deep Learning
• Data Pipelines
• Model Training
• Production Integration

Soft Skills

• Sound Judgment
• Collaboration
• Communication

Certifications & Qualifications

• BS in Computer Science
• MS in Engineering
• PhD in Related Technical Field

Industry Keywords

• User-History Modeling
• Feature Interaction Networks
• Attention-Based User-Sequence Models
• Multi-Task Learning
• Generative Recommender Systems

Tools & Technologies

• PyTorch
• TensorFlow
• AI-Assisted Development Tools