SUMMARY

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.
Where machine learning meets data at Yelp’s scale, fascinating problems arise. We are looking for an engineer to help us support our ML and data engineering teams in building and running state-of-the-art machine learning and data applications that power Yelp.
As a Junior Machine Learning Platform Engineer in the Core ML organization, you will contribute directly to Yelp’s ML platform. You’ll work on the tooling that makes our ML teams faster at building, training, and deploying models, and support data engineers in creating large-scale data applications. This role offers the opportunity to work with other teams on applying MLOps best practices, support impactful projects across the company, and grow your skills in a broad-scope environment that ranges from infrastructure-level work with Kubernetes to leveraging new technologies to solve complex ML use cases.
This opportunity requires you to be located in the Republic of Ireland. 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.

• Collaborate with our infrastructure teams to build upon a modern ML and Data Engineering tech stack, including Python, Spark, Flink, Kafka, AWS S3, and Kubernetes.
• Partner with applied ML and data engineering teams to help them deliver impactful projects by providing robust and easy-to-use platform tools.
• Contribute to the implementation and adoption of industry best practices for MLOps.
• Take ownership of key components of projects aimed at making the development of ML applications at Yelp faster and more reliable.
• Investigate and implement cost, performance, and reliability optimizations across our data processing and storage systems.
• Communicate with and support engineers across Yelp to help them effectively use our ML platform and tools.