Passionate about precision medicine and advancing the healthcare industry? Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
If your career has led you to tackle problems around big data, data science or machine learning, and you're ready to lend your skills to the fight against cancer, a job working on Lens at Tempus may be what you've been looking for. The Lens platform is a suite of web-based tools that let Tempus scientists and customers alike easily explore, visualize, and perform data science upon the world's largest library of clinical and molecular data.
As a Senior Software Engineer on the Lens Platform team, you will solve the inevitable problems of scale that come with building applications transacting with petabytes of molecular data and clinical imagery; you'll propose cloud-based architectures around these challenges, implement these designs across the graph of microservices that make up Lens, and lead groups of teammates to see these initiatives to completion.
Required skills: Experience designing and implementing scalable, highly available, cloud-based applications that sit atop terabytes or petabytes of data. CloudOps chops as it relates to application development: writing infrastructure as code, cloud access management, and networking. Coding experience with backend languages such as Python, Java, or Ruby. Experience containerizing your applications and a working knowledge of container orchestration tools like Kubernetes. Experience with Continuous Integration, Deployment, and Delivery. Experience with Agile methodologies (Scrum, XP, etc.). Nice to haves: Modern frontend development skills using React or Angular. Prior exposure to GCP infrastructure. Experience with some of the technologies we use such as Kubernetes, BigQuery, or GCP's Machine Learning infrastructure. Experience in biotech, genomics, clinical research, and precision medicine. Have built a platform to enable data science teams self-service capabilities supporting an applied machine learning workflow.
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