Yelp engineering culture is driven by our values: we’re a cooperative team that values individual authenticity and encourages creative solutions to problems. All new engineers deploy working code their first week, and we strive to broaden individual impact with support from managers, mentors, and teams. At the end of the day, we’re all about helping our users, growing as engineers, and having fun in a collaborative environment.
Yelp’s mission of connecting people with great local businesses requires the use of cutting-edge Machine Learning (ML) and Artificial Intelligence (AI) to scale across a vast and diverse base of users and businesses spanning various geographical locations. As a Staff-level ML Engineer on the Content Contributor Intelligence team, you will help build connections across millions of users and business listings. Your work will involve using cutting-edge industry tools, including neural networks (NNs), large language models (LLMs), and various embedding techniques for text, images, and videos. Additionally, you will apply traditional ML methods such as XGBoost and linear models to enhance our systems. You’ll be responsible for turning raw data into valuable signals and building ML systems end-to-end. This includes the full ML lifecycle from training models to deploying them in production, as well as contributing to the ML platforms these models rely on.
This opportunity is fully remote and does not require you to be located in any particular state within the US. We welcome applicants from throughout the US. We’d love to have you apply, even if you don’t feel you meet every single requirement in this posting. At Yelp, we’re looking for great people, not just those who simply check off all the boxes.
Experience developing and productionizing machine learning models, particularly in neural networks and computer vision, including their supported data pipelines.
Experience with machine learning using packages such as PyTorch, TensorFlow, Spark MLlib, XGBoost, and Sklearn.
Strong coding skills in Python or equivalent (Java, C++).
Solid understanding of engineering and infrastructure best practices.
The curiosity to uncover promising solutions to new problems, and the persistence to carry your ideas through to an end goal.
We highly value experience of working with LLMs, utilizing LLM APIs (OpenAI, Bedrock, etc), prompt engineering and evaluation.