We're on a mission to remedy the financial complexity crippling healthcare in America.
Our aim is to organize and use all healthcare information to reduce the cost of care and improve the patient experience.
As the only Unified Automation™ company for healthcare, we use the same machine learning approaches that made driverless cars possible to provide health systems with a single solution for revenue cycle management. AKASA's unique expert-in-the-loop approach, Unified Automation, combines modern machine-learning with human judgment and subject matter expertise to provide resilient automation. AKASA brings together the best of people, data and technology to efficiently, accurately and autonomously navigate the complex state of medical reimbursement in the United States.
We are growing rapidly and we've built a cross-functional skill set deep into the DNA of the company. We have technology experts from the top Silicon Valley technology companies (Google, Facebook, etc) and machine learning PhD programs (Stanford, etc). We also have senior leaders from the frontlines of healthcare with decades of experience leading teams of medical billers at some of the most prominent healthcare institutions in the US. And we have a deep bench of talent from healthcare services firms like the Advisory Board, Optum and Triage Consulting.
If you love to execute, we'd love to hear from you. We take a very mindful approach to building a culture that is flexible, diverse and inclusive. We approach our work thoughtfully, learn quickly, improve constantly, and celebrate our wins. Everyone is welcome — as an inclusive workplace, our employees are comfortable bringing their authentic whole selves to work. Be you.
About the Role
As our remote, hands-on Engineering Manager, Machine Learning, you'll directly report to the CTO and will scale and manage a team of machine learning engineers responsible for developing machine learning solutions to address large-scale healthcare problems.
AKASA is based in South San Francisco. As a company, we embraced remote work before COVID-19. We consider ourselves experts in working collaboratively wherever our team members happen to reside.
We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.