Staff DevOps Engineer

About us

Valo Health is a technology company that integrates human-centric data and AI-powered technology to accelerate the creation of life-changing drugs. Valo was created with the belief that the drug discovery and development process can and should be faster and less expensive, with a higher success rate. We use models early to fail less often as we reinvent drug discovery and development from the ground up. Disease doesn’t wait, so neither can we.

We are a multi-disciplinary team of experts in science, technology, and pharmaceuticals united in our mission to achieve better drugs for patients, faster. Valo is committed to hiring diverse talent, prioritizing growth and development, fostering an inclusive environment, and bringing together a group of different experiences, backgrounds, and voices to work together. We achieve the widest-ranging impact when we leverage our broad backgrounds and perspectives.

Valo’s machine learning and AI capabilities are built on high-quality, high-density translational biology data from multiple sources: that’s where you come in!

About the role

We are looking for a Staff DevOps engineer to help manage and develop the AWS Cloud infrastructure for our Data Science and Machine Learning environments. A successful candidate should be equally adept in handling day-to-day problems encountered by our users, perform sysadmin tasks, as well as able to see the larger picture and incrementally change our infrastructure to lower our overall operational costs and improve user experience. 

What you’ll do

• Handle a ticket duty to resolve user problems in an AWS Cloud-based environment. 
• Able to extract the general shapes of problems based on ad hoc tasks and find a technical path to automate away repetitive tasks
• Create tools and processes to incrementally allow self-service by users to decrease the overall support burden and empower users 

What you bring

• Proficient in Python, shell scripting
• Proficient in administering AWS environments: Linux EC2 instances, Storage options, general networking and security best practices, basic cost optimization strategies, and EKS clusters,. 
• Comfortable with Software Engineering best practices such as the use of source control systems (specifically Git), code review, automated testing, and CI/CD pipelines
• Experience with deploying and managing container-based services
• Experience with GitLab, including the deployment and administration of a self-managed GitLab server (with GitLab CI)
• General experience about deploying a broad range of servers or services, or ability to quickly learn the basics about something new (RDBM, MLflow, Prefect, Spark cluster, etc.)
• Familiar with infrastructure as code, automation of cloud deployment, and blueprints (e.g. Terraform, Pulumi)