May 19, 2021
Remote, OR 97458, USA
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.
AKASA is based in South San Francisco. As a company we embraced remote work opportunities before COVID-19. We consider ourselves experts in working collaboratively wherever our team members happen to reside.
About the Role
As our Engineering Manager, Machine Learning, you'll 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.
What You'll Do
Manage a team of and machine learning engineers with high expectations around individual ownership and influence
Set direction for the team, anticipating strategic and scaling-related challenges
Work within engineering and with sales, customer success and operations to ensure client satisfaction
Develop reliable pipelines that integrate data processing, human components, and tools.
Raise our engineering bar by sharing your expertise and best practices with the team.
Manage and publish machine learning research in the healthcare space
Skills and Qualifications
MS (PhD is ideal) in Computer Science or equivalent, with an emphasis on machine learning (computer vision, NLP)
8+ years work experience in machine learning or data engineering
Experience managing machine learning engineering teams
Proficiency in one or more programming languages including Python and C++
Excellent written and oral communication skills
What We Offer
Work with an experienced and complementary founding team consisting of serial entrepreneurs, AI experts and healthcare industry leaders
Meaningfully own or contribute to category-defining products that fundamentally change healthcare operations
Great compensation package and equity grants
Generous coverage for health, dental and vision insurance
Full employer coverage for life insurance
Free membership to One Medical (Concierge Clinic) for you and your family (if you are in a region covered by One Medical)
Unlimited Personal Time Off (PTO)
Bonus Company-Wide "Sanity Days" and other time off
Flexible schedules. Employees at all levels have reasonable discretion over their own time.
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.