Senior Machine Learning Engineer

Yahoo serves as a trusted guide for hundreds of millions of people globally, helping them achieve their goals online through our portfolio of iconic products. For advertisers, Yahoo Advertising offers omnichannel solutions and powerful data to engage with our brands and deliver results. It takes innovative technology to transform data into intelligent solutions that drive business impact. Whether you're implementing sophisticated ML models, optimizing data pipelines, or developing algorithms to process millions of data points daily, what you do here will make a meaningful difference to our products and customers. Want in? A Little About Us: The Yahoo! Consumer Data Team is developing a unified, cloud-native platform for all Yahoo user data. We simplify how teams access and utilize Yahoo first-party and third-party data while strengthening compliance. Our work empowers business units to enhance experimentation, monetization, marketing, and personalization with greater efficiency and reduced risk. A Little About You: The ideal candidate will have solid experience in machine learning engineering, with demonstrated ability to implement and optimize ML systems in production environments. They should be passionate about solving real-world problems with data and ML, and skilled at collaborating with cross-functional teams including data scientists, product managers, and other engineers. As part of our Audience Platform, you'll play a key role in helping Yahoo leverage first-party and third-party data to build comprehensive audience solutions essential for experimentation, monetization, marketing, and personalization. This large-scale initiative offers you the chance to tackle significant technical challenges while making impactful contributions to how we responsibly utilize data assets across our ecosystem. Responsibilities: * ML Implementation: Develop and optimize machine learning models and systems that solve business problems efficiently at scale * Production Deployment: Build reliable pipelines for training, evaluating, and deploying ML models to production environments * Model Performance: Implement monitoring solutions to track model performance and data quality in production * Feature Engineering: Design and develop robust features for machine learning models using large-scale data processing frameworks * Experimentation: Conduct A/B tests to measure the impact of ML models and features on key business metrics * Cross-team Collaboration: Work effectively with data scientists to operationalize research models and with product teams to integrate ML capabilities * Technical Documentation: Create comprehensive documentation for ML systems, models, and processes * Best Practices: Apply ML engineering best practices including version control, testing, and reproducibility to all projects * Model Optimization: Improve model efficiency, latency, and resource utilization for production environments * Problem Solving: Troubleshoot and resolve issues with data pipelines and model serving infrastructure * Knowledge Sharing: Participate in technical discussions and share knowledge with the broader engineering organization Requirements: * 5+ years of software engineering experience, with at least 3+ years focused on machine learning engineering * 2+ years of experience implementing and deploying ML models to production environments * Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn * Experience with cloud platforms (GCP, AWS, or Azure) and their ML services * Solid understanding of data processing frameworks (Spark, Beam, or equivalent) * Strong knowledge of ML fundamentals: supervised/unsupervised learning, evaluation metrics, feature engineering * Experience with ML operations including model versioning, monitoring, and continuous deployment * Proficiency in SQL and working with large datasets * Demonstrated ability to translate business requirements into technical ML solutions * Experience collaborating with data scientists and product teams * Bachelor's degree in Computer Science, Statistics, or related technical field; Master's degree preferred 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. Additionally, it involves 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 inform you 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, don't hesitate to 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 qualified applicants with criminal histories for employment in a manner consistent with applicable law. Yahoo is committed to creating an accessible environment for all candidates during the application process and for employees throughout their employment. If you need accessibility assistance and/or reasonable accommodation due to a disability, please submit a request via the Accommodation Request Form (www.yahooinc.com/careers/contact-us.html) or call +1.866.772.3182. Requests and calls received for non-disability-related issues, such as following up on an application, will not receive a response. 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.