Senior Software Engineer, ML Infrastructure

Curai Health is on a mission to expand healthcare access and deliver the best in class care to everyone. We run a virtual primary care clinic, and leverage AI and machine learning to help our doctors work more quickly and effectively with patients. At Curai Health we are building a diverse, world-class, multi-disciplinary team across engineering, AI research, product, design, operations, and medicine. Our Curaians come from a variety of backgrounds, are mission-oriented, embody our core values, and are passionate about making a difference in the lives of millions of people.

At Curai Health we have embraced remote-first and work with people from all over the country and world. Full-time team members receive benefits that include medical, dental, vision, 401(k) matching, a remote work stipend, parental leave, and more. We are well funded by top-tier Silicon Valley investors including Morningside, General Catalyst and Khosla Ventures.

We are looking for a Software Engineer - ML... Infrastructure passionate about health care to help us manage the operations of our end-to-end machine learning infrastructure. Your work will improve the quality and lower the cost and friction of high-quality health care for patients around the world.

To learn more about working in our ML team, please check out our employee spotlights here, and see our Key Values blog post here.

In this role you will:

• Oversee all aspects of Curai’s ML cloud infrastructure
• Manage, monitor, troubleshoot machine learning infrastructure
• Automate ML models deployments
• Setup continuous integration pipelines of Curai’s ML applications

An ideal candidate has:

• 5+ years of industry experience
• 2+ years of experience with a cloud computing platform (Amazon Web Services, Google Cloud Platform, or Microsoft Azure) including container orchestration frameworks (such as Docker, ECS, Kubernetes, etc)
• Experience with data management systems in service of machine learning, including database systems including BigQuery, Postgres, or MongoDB
• Experience modeling, deep learning frameworks, AWS Sagemaker, building auto-scaling ML systems, and working with medical domain will be valued, but are not strictly necessary