A Little About Us

At Yahoo News, we are laser-focused on making discovery delightful and becoming the world’s best curator for our 35 million daily users and expanding our distribution to more platforms to meet millions more users where they are. Building the best guide to the Internet (and the world) requires building the best team.

Location Preference: Hybrid work in NYC or Reston, Virginia

Who You Are

• You excel at explaining technical concepts to anyone and everyone. People enjoy collaborating with you.

• You have a bias for action. When you see problems, you solve them.

• You are extremely curious. You are constantly interested in how the systems and models you interact with work “under the hood.”

• You are customer focused–regardless of whether the customer is an external user or an internal team.

• You know that writing code isn’t the end of the process, and you delight in understanding how that code is running in production, looking at metrics, and planning improvements.

Responsibilities

• Hands-on development of “full-stack” ranking, recommendation and content understanding systems that will power the next-generation of Yahoo! News. 

• Leverage third-party, open-source and in-house machine learning tools to build high-performing machine learning systems. 

• Work collaboratively with cross-functional partners to leverage machine learning to improve Yahoo News for our readers and build state-of-the-art tooling for our editorial team. 

Qualifications

We are building a team with expertise across machine learning engineering, machine learning modeling and data engineering to enable us to deliver end-to-end product solutions. We encourage you to apply if you have expertise in at least one of these domains and you are excited to work on a “full-stack” ML engineering team. 

MLOps / DevOps

• Experience designing, building, and managing scalable infrastructure for training and deploying ML models.

• Can build continuous integration and continuous deployment (CI/CD) pipelines to automate the testing, validation, and deployment of ML models.

• Strong working knowledge of observability tools (e.g., Prometheus, Grafana, Datadog etc.) to monitor system performance, logs, and metrics. 

ML Modeling 

• Ability to formalize a product problem, run reproducible offline experiments and analyze the results. 

• Strong written communication and data visualization skills.

• Experience working with modern ML frameworks (e.g. PyTorch, TensorFlow, Jax). 

• Understanding of the difference between “research” code and production code, and when each is appropriate. 

Data Engineering 

• Strong working knowledge of data engineering best practices & data warehousing concepts.

• Strong familiarity with software engineering principles, design patterns, and code quality practices.

• Previous working experience in Python and Java, Scala or Go.

• Working knowledge of how data scientists leverage data.

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.

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 (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.

At Yahoo, we know that diversity makes us stronger. We are committed to a collaborative, inclusive environment that encourages authenticity and fosters a sense of belonging. We strive for everyone to feel valued, connected, and empowered to reach their potential and contribute their best. Check out our diversity and inclusion (www.yahooinc.com/diversity/) page to learn more.

Yahoo has a high degree of flexibility around employee location and hybrid working. In fact, our flexible-hybrid approach to work is one of the things our employees rave about. Most roles don’t require specific regular patterns of in-person office attendance. If you join Yahoo, you may be asked to attend (or travel to attend) on-site work sessions, team-building, or other in-person events. When these occur, you’ll be given notice to make arrangements. 

If you’re curious about how this factors into this role, please discuss with the recruiter.

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