Santa Monica, CA
Industry: Internet Services•
Not Specified years
Posted 374 days ago
It's one thing to build a model in R Studio or a Jupyter notebook on your laptop with a pre-fab CSV data set that easily fits in RAM. It's another thing to build and deploy a service that runs on multiple machines, is up 24x7, loads in seconds, makes predictions with consistently low latency, doesn't crash on unexpected/missing inputs. Often the machine learning technique is simple, but making it scale is hard. For example, techniques that involve large matrices or have O(N^2) space/time requirements often break down as you increase the number of documents or words. For example, while sci-py is a great exploratory tool, we have crashed it before due to internal 32-bit limits.
With data such as a billion+ historical job postings, tens of millions of active job seekers interacting with our system, and hundreds of billions of impression and click events, there are incredible opportunities to use your skills to build new data-driven features. Bonus: working at ZipRecruiter, you will be helping literally millions of people find their dream job.
What we're looking for:
Technologies we use:
Big Data, ML, AI, Keras, TensorFlow, Python, Redshift, S3, Spark, Random Forests, Vowpal Wabbit