Quansight is hiring a
Senior Open Source Infrastructure Engineer

Summary

We are seeking a fully remote, Senior Open Source Infrastructure Engineer to join our team at Quansight. The role involves supporting and improving our cloud and on-premises infrastructure, collaborating with the team, exploring emerging technologies, and contributing to an open-source Data Science platform (nebari).

Requirements

• Experience using infrastructure-as-code tooling such as Terraform, Pulumi, Cloudformation to deploy infrastructure
• Experience running production workloads in at least one major cloud platform (AWS, Azure, GCP)
• Experience developing tools in a general purpose programming language (eg. Python)
• Experience building Continuous Integration and Continuous Delivery (CI/CD) pipelines using tools such as GitHub actions, Gitlab CI/CD, Circle CI, etc
• Familiarity with modern software engineering practices – including automated tests, code review, version control, observability, etc
• Experience containerizing and deploying applications to platforms such as Kubernetes, AWS ECS, and Google Cloud Run
• Comfortable working independently and reaching out for feedback and support as needed
• Experience collaborating and coordinating work via online platforms, such as GitHub, GitLab, or BitBucket, and distributed revision control
• Ability to constructively receive feedback

Responsibilities

• Support Quansight’s growing cloud and on-premises infrastructure and help make them more reliable, scalable, and efficient
• Work with the team to address support issues from our clients and collaborators
• Explore emerging technologies in the Cloud and DevOps spaces
• Design and implement cloud computing systems with the rest of our infrastructure team

Preferred Qualifications

• Experience working on geographically distributed teams
• Experience working with or contributing to open-source projects
• Exposure to the Python Data Science stack - Pandas, Numpy, Dask, etc
• Experience with the Jupyter ecosystem and other tools for interactive computing
• Experience with common data science methods, platforms, workflows, and infrastructures; with data management systems, practices, and standards; and the capacity to gain familiarity with new related topics
• Experience with Machine Learning Operations (MLOps) platforms, workflows, and infrastructures and the capacity to gain familiarity with new related topics

Benefits

• Flexibility in work times and locations
• Vacation time is not just encouraged but celebrated and enforced
• Competitive compensation
• A comprehensive sick policy and parental leave
• A generous amount of flexible paid time off
• If you are located in the United States, Canada, Germany or the UK we also offer a comprehensive benefits package