4+ years development experience in Python
Demonstrable knowledge of computer science fundamentals, whether by degree or otherwise
System/performance engineering (profiling process memory/cpu/io/network usage, system calls, flame graphs)
Personal drive to get things finished
Effective communication behavior
8+ years development experience
Publicly reviewable contributions to interesting development projects
Experience supporting user-facing code and APIs
Experience working with major cloud providers (AWS, Google Cloud, Azure)
Experience/understanding resource management services workflow (Hadoop/Yarn, Mesos, Kubernetes or any other)
We are ready to reward you with all sorts of benefits in the form of insurance +1, free lunches and dinners, English lessons, gym coverage, team-buildings and other small amenities for your desire to develop with us.
Design, build, test and support the next generation of DataRobot cloud-native compute platform
Develop, test, 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
DataRobot accelerates the process of building predictive models to get the most out of valuable data. We work hard to create tools that nascent data scientists can use effectively while also exposing the rich detail and control that data science veterans rely on. Our headquarters is in Boston, with development offices in Kyiv, Lviv, Minsk, Munich, Copenhagen and Singapore.
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 designing, building and monitoring a scalable worker management infrastructure, designing and supporting internal and public HTTP APIs, and instrumenting DataRobot to integrate with enterprise IT infrastructure. Our team uses the following technology on a routine basis: Python, Flask, MongoDB, Redis, RabbitMQ, NGINX, pytest, docker, K8s and YARN among many others.