Want to build cutting-edge tooling for machine learning? Ever wondered how much and which compute resources are required to train machine learning models that can classify millions of photos and reviews? Or how to automate the ML infrastructure for rapid model training and connect those models to a variety of model serving platforms including ranking and streaming systems? We’re looking for remote ML infrastructure engineers who thrive on living at the intersection of machine learning, scalable infrastructure, and massive flows of data.
On the Core ML team, our mission is to build the machine learning platform to pursue Yelp’s top business initiatives. We build tools which help engineers develop and apply their ML models in light speed using the latest technology frameworks, such as Jupyter, Spark, Kubernetes, Kafka, and Cassandra. In many cases, we’ll contribute or drive open-source projects to help us achieve our mission, including ML model serialization and inference projects. We are also building tooling and developing processes to centralize data products and feature stores for analysts and ML needs.
Come work with and learn from our team that is full of a passionate and diverse group of engineers with years of experience spanning machine learning modeling to systems engineering. We communicate across the company, inputting ML-based needs and outputting efficient tooling and systems. As machine learning evolves, we continue to ride the wave of innovation by combining industry best practices and cutting-edge tooling to bolster Yelp’s machine learning platform. See a recentblog post giving an overview of our ML Platform.
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.
What You Will Do:
Build the platform that powers Yelp’s top business initiatives with machine learning
Streamline and build new abstractions to support machine learning workflows
Collaborate with other teams on building centralized data & feature stores
Connect regularly with different internal groups for input on their ML infra and data needs
Gain expertise in cutting-edge machine learning infrastructure
Apply ML techniques to deliver models and data for high impact business problems
What We Are Looking For:
A balanced interest in machine learning, infrastructure, and data products
Deep understanding of the programming languages and systems you’ve worked on
Familiarity with tooling, including Jupyter, Apache Spark, TensorFlow, Docker, Kubernetes, Flink, and Kafka
Minimum 2 years industry experience or an academic background in machine learning, data mining, or data infrastructure
Passion for architecting large systems with elegant interfaces that can scale easily
Excellent written and interpersonal communication skills
A team player who lives theYelp Values and thrives in a diverse and inclusive work culture
At Yelp, we believe that diversity is an expression of all the unique characteristics that make us human: race, age, sexual orientation, gender identity, religion, disability, and education — and those are just a few. We recognize that diverse backgrounds and perspectives strengthen our teams and our product. The foundation of our diversity efforts are closely tied to our core values, which include “Playing Well With Others” and “Authenticity.”
We’re proud to be an equal opportunity employer and consider qualified applicants without regard to race, color, religion, sex, national origin, ancestry, age, genetic information, sexual orientation, gender identity, marital or family status, veteran status, medical condition or disability.
We are committed to providing reasonable accommodations for individuals with disabilities in our job application process. If you need assistance or an accommodation due to a disability, you may contact us at firstname.lastname@example.org or 415-969-8488.
Note: Yelp does not accept agency resumes. Please do not forward resumes to any recruiting alias or employee. Yelp is not responsible for any fees related to unsolicited resumes.