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 Senior ML engineer, you will have the opportunity to foster these connections across millions of users and businesses using state of the art methods such as neural networks (NNs) and large language models (LLMs). 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 area in Canada. We welcome applicants from throughout Canada. 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'll do:

  • Conduct end-to-end analyses, from wrangling data via SQL or Python, to statistical modeling, to hypothesizing and presenting business ideas.
  • Work with large and complex datasets.
  • Support the development and deployment of projects involving machine learned models for offline, batch-based data products as well as models deployed to online, real-time services.
  • Productionize and automate model pipelines within Python services.
  • Drive and advocate adoption of best practices in MLOps (Machine Learning Operations).

What it takes to succeed:

  • Ideally 3+ years of experience developing and productionizing machine learning models, including their supported data pipeline.
  • Experience with machine learning using packages such as TensorFlow, Keras, Spark MLlib, XGBoost, Sklearn, etc.
  • Strong coding skills in Python or equivalent (Python, Java and 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.

What you'll get:

  • Compensation range is $97,000 - $230,000 CAD annually. You may also be offered a bonus, restricted stock units, and benefits.
  • This opportunity has the option to be fully remote in all locations across Canada.
  • You can find more information about Yelp's five star benefits here!


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, disability, or any other protected status.


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 [email protected] or 1-415-969-8488.


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.




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