Senior ML Engineer - Audience Enrichment

Yahoo is a leading technology company connecting brands and partners with a vast audience. As a Senior ML Engineer, you will develop and optimize machine learning solutions to transform user data into actionable insights, collaborating with cross-functional teams to deliver personalized experiences and enhance audience engagement.

Responsibilities:

• Develop and optimize end-to-end ML solutions for audience segmentation, predictive modeling, and behavioral enrichment at 2.5B+ profile scale
• Build reliable production pipelines for training, evaluating, and deploying ML models using GCP infrastructure (Vertex AI, Dataflow, Composer)
• Design robust feature engineering pipelines using large-scale data processing frameworks (Spark, Beam, BigQuery)
• Implement comprehensive monitoring solutions tracking model performance, data drift, prediction quality, and business impact metrics
• Tune, validate, and optimize ML models for accuracy, efficiency, and scalability while managing computational costs
• Collaborate with Data Science teams to productionize research models and translate prototypes into scalable production systems
• Partner with Product teams to understand business requirements and deliver ML capabilities for audience intelligence
• Apply ML engineering best practices including version control (Git), automated testing, CI/CD workflows, and model versioning
• Create comprehensive documentation for ML systems, feature pipelines, model artifacts, and operational runbooks
• Improve model efficiency, inference latency, and resource utilization for cost-effective production serving
• Troubleshoot data pipeline failures, model serving issues, and data quality problems in production environments
• Participate in technical discussions, code reviews, and knowledge sharing across teams

Requirements:

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Machine Learning, or related technical field
• 5+ years software engineering experience building production systems
• 3+ years in ML engineering, data science, or applied machine learning roles
• 2+ years implementing and deploying ML models to production environments at scale
• 2+ years hands-on experience with GCP (BigQuery, Dataproc, Composer, Dataflow, Vertex AI) or AWS equivalents
• Strong Python and/or Java programming skills for production ML systems
• Proficiency with ML frameworks: TensorFlow, PyTorch, scikit-learn, XGBoost for building and deploying models
• Hands-on experience with data processing frameworks: Apache Spark, Apache Beam, or equivalent distributed computing tools
• Solid ML fundamentals: supervised/unsupervised learning, feature engineering, model evaluation, hyperparameter tuning
• SQL proficiency for large-scale data manipulation and feature extraction
• Understanding of MLOps practices: model versioning, A/B testing, monitoring, feature stores, model serving
• Demonstrated ability translating business requirements into technical ML solutions with measurable impact
• Strong problem-solving skills and analytical thinking in complex data environments
• Excellent collaboration with cross-functional teams including product, data science, and engineering
• Team-level impact with ability to influence technical decisions within immediate team
• Understanding of data privacy compliance (GDPR, CCPA) in ML systems
• Experience with audience segmentation, propensity modeling, recommendation systems, or user behavior prediction
• Knowledge of privacy-preserving ML techniques and compliance requirements (GDPR, CCPA, differential privacy)
• Familiarity with MLOps tools: MLflow, Kubeflow, Vertex AI Pipelines, Weights & Biases
• Prior experience in adtech, marketing technology, or consumer analytics platforms
• Understanding of A/B testing methodologies, experimentation frameworks, and causal inference
• Experience with online learning, real-time model serving, or feature streaming
• Contributions to ML open-source projects, technical publications, or conference presentations
• Self-driven, detail-oriented, strong problem-solving abilities in fast-paced environments