Yahoo needs to develop a unified, cloud-native platform for all Yahoo user data to simplify data access and utilization, strengthen compliance, and empower business units to enhance experimentation, monetization, marketing, and personalization with greater efficiency and reduced risk.
Requirements
- 10+ years of software engineering experience, with at least 5+ years focused on machine learning engineering and system design
- 4+ years of experience developing large-scale machine learning systems for enterprise applications
- 3+ years hands-on experience with cloud ML ecosystems (Google Cloud AI Platform, AWS SageMaker, or Azure ML)
- Expert-level experience implementing and optimizing ML pipelines that process terabyte-scale datasets
- Deep understanding of ML fundamentals: statistical modeling, deep learning architectures, feature engineering, and model optimization
- Expert-level knowledge of ML operations including model versioning, A/B testing frameworks, online learning, and monitoring
- Advanced proficiency in Python and ML frameworks (TensorFlow, PyTorch, or JAX) with demonstrated ability to architect complex ML applications
Responsibilities
- Define the technical architecture roadmap for machine learning platforms that aligns with long-term business objectives
- Drive innovation initiatives that span multiple engineering teams and technical domains in the ML space
- Design distributed ML systems that process billions of events daily with industry-leading performance metrics
- Establish enterprise-wide standards for model quality, explainability, fairness, and compliance
- Pioneer next-generation machine learning capabilities that deliver competitive advantages in user personalization and prediction
- Create frameworks and methodologies that systematically improve ML platform scalability and efficiency
- Lead resolution of complex ML challenges that have organization-wide impact
Other
- Effectively represent ML considerations in executive-level strategy discussions
- Mentor senior ML engineers and technical leads to build organizational ML depth
- Represent our company in ML conferences and industry forums as a thought leader
- Lead technical evaluation of potential ML acquisitions, partnerships, and major technology investments
- Anticipate emerging ML trends and guide our company's technical positioning
