The role
From Yahoo's own posting.
Yahoo Mail is the ultimate consumer inbox with hundreds of millions of users. It’s the best way to access your email and stay organized from a computer, phone or tablet. With its beautiful design and lightning fast speed, Yahoo Mail makes reading, organizing, and sending emails easier than ever.
A little About Us:
The Mail Intelligence platform is responsible for building the next generation platforms and services enabling Yahoo to deliver deeply personalized content to the hundreds of millions of users wherever they are and whatever mode of consumption they are using.
We process billions of messages and data at the petabyte scale. With the help of cutting-edge algorithms we extract information, build knowledge, and interconnect information between different sources to power both user experience and revenue optimization. Building this knowledge provides many challenges in the areas of machine learning techniques and big data processing in order of petabytes. The platform plays a critical role in monetization strategy, including: intelligent revenue forecasting and optimization models, ads relevance and targeting systems, offer selection and targeting, and dynamic pricing. These challenges span recommendations, ranking, personalization, large-scale machine learning, causal inference, and real-time decision systems. You will lead the algorithmic design and strategic direction of models that not only enhance user experience but also drive measurable business impact through revenue and engagement optimization.
Yahoo Mail is the ultimate consumer inbox. It is the best way to access your email and stay organized from a computer, phone, or tablet. With its beautiful design and lightning fast speed, Yahoo Mail makes reading, organizing, and sending emails easier than ever. Come join this amazing team of Researchers, Engineers, Product Managers and Designers to work on next generation innovative experiences transforming how users connect with each other every day.
About You:
You are an expert in developing and applying state-of-the-art machine learning and deep learning models to solve complex, high-stakes monetization and personalization problems.
You thrive in a research-oriented environment, pushing the boundaries of innovation while maintaining a clear focus on simplifying model architectures and delivering measurable business impact.
You have a strong academic foundation and a demonstrated commitment to personalization, user modeling, and monetization strategies for large-scale systems.
You excel in translating theoretical research into practical, high-impact algorithmic applications—particularly in ranking, recommendation systems, Ads targeting, causal uplift, pricing strategy, and reinforcement learning.
You are a hands-on research leader with deep expertise in designing, training, and evaluating large-scale models, including transformer-based and deep learning architectures.
You possess an AI-forward mindset, actively seeking to optimize your research and modeling workflow through modern AI diagnostics, prompt engineering, and automated evaluation frameworks.
You have a collaborative, consensus-building mindset, bringing excellent communication skills to resolve complex theoretical tradeoffs and guide cross-functional squads.
Your Day:
Lead the research and algorithmic design of advanced models for ranking, personalization, recommendation systems, ads targeting, causal uplift modeling, dynamic pricing, and revenue forecasting.
Design, train, evaluate, and prototype state-of-the-art machine learning, deep learning, and reinforcement learning models, taking full ownership of experimental integrity and long-term scientific risks.
Establish robust experimental standards and guide scalable modeling workflows on platforms like GCP to streamline model training, validation, and evaluation.
Incorporate LLM-driven synthesis into monetization models to prototype hybrid architectures and accelerate relevance tuning.
Collaborate with engineering partners to transition machine learning models from prototype to production, making strategic tradeoffs between theoretical complexity and operational constraints.
Proactively simplify existing model architectures, address core modeling bottlenecks, and establish rigorous scientific standards across multiple projects.
Leverage AI-assisted coding and prototyping tools to accelerate model development and evaluation.
Stay abreast of the latest research trends, contributing to Yahoo's engineering and scientific brand through publications, patents, or technical presentations.
Mentor, guide, and conduct technical assessments for senior and mid-level research scientists and machine learning engineers, fostering a culture of continuous learning and AI experimentation.
You Must Have:
PhD (preferred) or Master’s degree in Computer Science, Statistics, Applied Mathematics, or a related field.
8+ years of industry experience (or 5+ years with a PhD) in machine learning, deep learning, or related fields, with a track record of designing and scaling advanced ranking, personalization, ads targeting, or revenue optimization systems.
Strong fundamentals in machine learning and deep learning, with proven expertise in optimizing business metrics (e.g., CTR, CVR, eCPM) alongside model-centric loss functions.
Comprehensive understanding of deep learning architectures, including transformer-based models, and hands-on experience validating model outputs for performance, alignment, and governance.
Expertise in Python and core modeling frameworks like TensorFlow or PyTorch, Hugging Face, Pandas, and NumPy.
Demonstrated experience leveraging AI-assisted development tools (e.g., Anthropic Claude via GCP) to rapidly prototype experiments and accelerate research iteration.
Proven ability to communicate complex mathematical and scientific concepts effectively to both engineering partners and business stakeholders, driving alignment on key monetization goals.
You May Have:
Familiarity with Reinforcement Learning and online decision systems.
Experience building and fine-tuning large language models (LLMs) for search, retrieval, or monetization tasks.
Hands-on experience with cloud platforms (e.g., GCP, AWS) and large-scale data processing engines (Hadoop, Spark).
Contributions to the machine learning research community through peer-reviewed publications, patents, or competition platforms like Kaggle.
Strong understanding of causal inference, experimental design, and A/B testing methodologies at scale.
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 disabili