Sr. Research Engineer
A Little About Us
Yahoo has the most trafficked destinations on the internet, including Yahoo, AOL, and many other well-known brands. The Yahoo Advertising team is responsible for delivering market-leading advertising and audience products, solutions, and services. Our advertising products deliver billions of ad impressions to hundreds of millions of users every day, enabling hundreds of thousands of advertisers to effectively connect with the right audience at the right time across devices and across the globe.
A Lot About You
You are an outstanding research engineer with rich experience in big data and productionization of machine learning models, excellent analytical skills, sound knowledge of software engineering, statistics, and experimental design, and a proven ability to communicate findings. You are always curious, self-motivated, and eager to learn new domain knowledge and tools. You are an out-of-the-box thinker, a believer in data-driven approaches, and a quick learner. You enjoy working with a strong, cross-functional, and sometimes cross-geography team of engineers and scientists, and you are passionate about working with our business and product teams to turn data into actionable insights and production models. You always think positively, have a can-do attitude, and focus on “getting stuff done” with quality. People like to work with you because you’re a valuable contributor and a responsible team player.
Responsible for working together with research scientists to implement state-of-the-art large-scale applied machine learning solutions for problems in information retrieval, machine learning, computational linguistics, unsupervised clustering, data mining
Leverage our large data sets to find structures and patterns in our advertising platform, identify the areas that need improvement for system scalability and business opportunity
Execute end-to-end implementation of our data ETL pipelines and machine learning training/testing pipelines on our petabyte dataset, and optimize the computational resources consumed by these pipelines
Drive innovation, prototype scalable solutions, and work closely with product managers, architects, data scientists, and other engineers to turn research prototypes into production
Advanced degree in Computer Science or a related field
Proficient programming skills in at least one of the following languages: Python, Java
Familiar with Pig, Pyspark, Hadoop, and SQL, Airflow
Strong knowledge in data structures, algorithm design, and machine learning with experimental design, and etc
5+ years of experience building production data pipelines, ideally using one or more frameworks such as Spark, Hive/Hadoop
Experience in delivering machine learning-based solutions in production
Excellent communication and presentation skills and Ability to read, understand, and contribute to scientific papers
Results-driven, great attention to detail, and a team player
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 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 408-336-1409. Requests and calls received for non-disability related issues, such as following up on an application, will not receive a response.
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.
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