3+ years development experience in Python
Demonstrable knowledge of computer science fundamentals, whether by a degree or otherwise
Personal drive to get things finished
Effective communication behavior
Consider these optional criteria for candidates to distinguish themselves:
5+ years development experience
System/performance engineering (profiling process memory/cpu/io/network usage, system calls, flame graphs)
Publicly reviewable contributions to interesting development projects
Experience with both python 2 and 3
Experience with Java or R
Experience supporting user-facing code and APIs
Data Science experience
Experience/understanding resource management services workflow (Hadoop/Yarn, Mesos, Kubernetes, AWS, OpenStack, Docker or any other)
Experience with different Python application servers, including uWSGI, gunicorn.
As a member of the Inference domain, you’ll be directly responsible for the systems that enable customers to productionalize machine learning models in our MLOps product. That includes providing predictive capabilities to customers to for example assess risks of loan applications, control temperatures of manufacturing furnaces, aid in diagnosing medical conditions, help recover from current and future pandemics, and a huge number of other applications. The goal is to make predictions easier, scalable, more widely available, and, of course, trustworthy.
Develop, test, operate, and support features of DataRobot
Create and maintain automated unit tests and functional tests
Design infrastructure for new features with the input of peers
Plan capacity, manage application performance
Manage individual projects and milestones with abundant communication of progress
Seek, give, and receive critical feedback in a constructive manner, including but not limited to code review
We are looking for engineers who are willing to continuously learn, challenge themselves, and apply their knowledge to improve DataRobot’s MLOps product.
In order to keep up with the demand for new features in DataRobot, we are looking to grow our backend engineering team. Primary responsibilities of this team include developing new data science tools, designing and supporting our APIs, and instrumenting DataRobot to integrate with enterprise IT infrastructure. Our team uses the following technology on a routine basis: Python, Flask, MongoDB, pytest, docker, Redis, NGINX, AWS, Linux and Terraform among many others.