The MLOps team owns the features of the DataRobot platform for operating models in production environments, coordinating the management, monitoring, and governance of all types of models hosted in all types of environments. We apply innovative data science and engineering techniques to ensure that models in production continue to predict at a high level and that they can be trusted by stakeholders to function without bias.
As part of our MLOps team, you will work on DataRobot’s machine learning platform and actively contribute to the development of our powerful model deployment, serving, and monitoring capabilities.
We are looking for talented people with excellent Web API development skills, experience building production-grade applications at scale, and a strong understanding of data structures and algorithms. Additionally, the ability to analyze problems, invent simple solutions, and show initiative while collaborating with the team to deliver features is crucial.
Key Responsibilities:
- Partners with Product Managers and Data Scientists to determine process and execute on designing and implementing new features, and shipping end-to-end to both Cloud and Enterprise.
- Design and build application-level software working with Kubernetes Infrastructure and containers.
- Partners with the DevOps and Security team to build Enterprise installation and documentation.
- Lead projects, communicate requirements and scope.
- Design, build and document extendable REST APIs using Python Flask and OpenAPI schema.
- Maintain and improve the existing codebase.
- Troubleshooting complex production environments at the application and DB level.
- Evaluate and validate code with tests.
Knowledge, Skills and Abilities:
- 8+ years of professional software development
- Strong Python knowledge
- Understanding of networking
- Building containerized applications
- Ability to plan and lead projects from start to finish and explain your design decisions
- Great communication skills: ability to work in teams, share knowledge and write documentation.
- Computer science fundamentals, basic understanding of algorithms and time complexity.
- Ability to write quality integration/functional tests.
Requisite Education and Experience:
- Bachelor’s degree in relevant field
- Kubernetes fundamentals, developer-level experience.
- Experience with Docker.
- Experience with AWS/Azure/GCP.
- DevOps fundamentals, scripting.
- Building CI/CD pipelines using Jenkins.