Software Engineer - Machine Learning (Remote)

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Yelp has hundreds of millions of pieces of user-contributed content, millions of users and business listings, and hundreds of thousands of advertising customers–and all of these numbers are constantly growing. Yelp’s machine learning engineers turn raw data into valuable signals by building end-to-end ML systems, from feature ETL to deploying predictive models in production, as well as by building the ML platforms that these models rely on. These systems power applications like search ranking, ads targeting, push notifications, and photo understanding. Our data teams banter about Bandits, know their way down a Gradient, and aren’t too Naïve to kick back in our office.

Yelp engineering culture is driven by our values: we’re a cooperative team that values individual authenticity and encourages creative solutions to problems. We enable all new team members to deploy working code their first week, and your impact will only grow from there with the support of your manager, mentor, and team. At the end of the day, we are all about helping our users, growing as engineers, and having fun in a collaborative environment.

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.

This opportunity is fully remote and does not require you to be located in the Toronto area. We welcome applicants from throughout Canada.

Where You Come In:

Conduct end-to-end analyses, from wrangling data via SQL or Python, to statistical modeling, to hypothesizing and presenting business ideas.

Work with large, complex datasets.

Lead the development of machine learned models for offline, batch-based data products as well as models deployed to online, real-time services.

Work in areas such as search, ads targeting, spam, and photo understanding.

Productionize and automate model pipelines within Python services.

What it Takes to Succeed:

Experience with data ETL and data analysis packages and workflows (SQL, MapReduce, Spark, etc.).

Experience with machine learning using packages such as xgboost, sklearn, TensorFlow, etc.

A love for writing beautiful and maintainable code.

The curiosity to uncover promising solutions to new problems, and the persistence to carry your ideas through to an end goal.

Comfort in using a Unix environment.