Senior ML Engineer - Audience Enrichment

Senior ML Engineer

It takes powerful technology to connect our brands and partners with an audience of hundreds of millions of people. Whether you're looking to write mobile app code, engineer the servers behind our massive ad tech stacks, or develop algorithms to help us process trillions of data points a day, what you do here will have a huge impact on our business—and the world.

Our platform is the foundational identity and data layer for 900M+ monthly active users, serving 2.5B+ profiles at massive scale. We are building a predictive, identity-centric insights engine—ensuring our audience is understood with precision to deliver hyper-personalized experiences and advertising solutions across all our digital properties.

Our mission centers on first-party data strategy: capturing, enriching, and activating audience signals to build a 360-degree view of every user. We operate under a Privacy-by-Design philosophy, adhering to global regulations (GDPR, CCPA) and industry security standards, while leveraging a cloud-native stack across GCP (BigQuery, Spanner, Dataflow, Composer, GKE) and AWS, with modern MLOps practices to deliver measurable business impact.

As a Senior ML Engineer, you will develop and optimize end-to-end machine learning solutions that transform raw user data into actionable audience intelligence. Your predictive models—including Lookalike audiences, Propensity scores, and Churn predictions—enable Product, Engineering, and Sales teams to deliver hyper-personalized experiences and maximize the commercial value of our 900M+ monthly active users.

You will build production ML pipelines processing data from our 2.5B+ profile platform, creating enrichment signals that directly impact user engagement, ad revenue, and retention. Your work requires balancing model accuracy, computational efficiency, and data privacy while operating at massive scale across petabyte-scale data infrastructure.

This role demands expertise in production ML engineering, large-scale data processing frameworks (Spark, Beam, BigQuery), and MLOps practices. You will collaborate closely with Data Science, Product, and Engineering teams to translate business requirements into scalable ML solutions that drive measurable business outcomes.

Key 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

Required Qualifications

Education

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Machine Learning, or related technical field

Experience

• 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

Technical Skills

• 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

Competencies

• 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

Preferred Qualifications

• 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

The material job duties and responsibilities of this role include those listed above as well as adhering to Yahoo policies; exercising sound judgment; working effectively, safely and inclusively with others; exhibiting trustworthiness and meeting expectations; and safeguarding business operations and brand integrity.

At Yahoo, we offer flexible hybrid work options that our employees love! While most roles don't require regular office attendance, you may occasionally be asked to attend in-person events or team sessions. You'll always get notice to make arrangements. Your recruiter will let you know if a specific job requires regular attendance at a Yahoo office or facility. If you have any questions about how this applies to the role, just ask the recruiter!

Yahoo is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against based on age, race, gender, color, religion, national origin, sexual orientation, gender identity, veteran status, disability or any other protected category. Yahoo will consider for employment qualified applicants with criminal histories in a manner consistent with applicable law. Yahoo is dedicated to providing an accessible environment for all candidates during the application process and for employees during their employment. If you need accessibility assistance and/or a reasonable accommodation due to a disability, please submit a request via the Accommodation Request Form ( or call View phone number on click.appcast.io. Requests and calls received for non-disability related issues, such as following up on an application, will not receive a response.

We believe that a diverse and inclusive workplace strengthens Yahoo and deepens our relationships. When you support everyone to be their best selves, they spark discovery, innovation and creativity. Among other efforts, our 11 employee resource groups (ERGs) enhance a culture of belonging with programs, events and fellowship that help educate, support and create a workplace where all feel welcome.

The compensation for this position ranges from $128,250.00 - $266,875.00/yr and will vary depending on factors such as your location, skills and experience. The compensation package may also include incentive compensation opportunities in the form of discretionary annual bonus or commissions. Our comprehensive benefits include healthcare, a great 401k, backup childcare, education stipends and much (much) more.

Currently work for Yahoo? Please apply on our internal career site.