Sr. MLOps Engineer

About AKASA

AKASA is the preeminent provider of generative AI solutions for the healthcare revenue cycle. The company has raised more than $205M in funding from investors such as Andreessen Horowitz, BOND, and Costanoa Ventures. 

Named one of the fastest-growing GenAI startups to watch by AIM Research, we’re solving the biggest challenges in the financial infrastructure of healthcare. Transaction volume through the AKASA Platform has grown consistently, with a ~2.5x year-over-year increase in the last year. The AKASA customer base represents more than $90B in net patient revenue and includes the most innovative health systems in the country, like Stanford and Johns Hopkins.    

Our founding team includes Silicon Valley leaders who have founded or been founding team members of multiple companies with successful exits. Our CEO was ranked among the “Top 50 Healthcare Technology CEOs” by the Healthcare Technology Report. We have been recognized as one of “America’s Best Startup Employers” by Forbes, “Most Innovative Digital Health Startups” by CB Insights, “Best Companies for Remote Workers” by Quartz, and “Best Places to Work” by Fortune, Modern Healthcare, and Built-In, along with being certified as a “Great Place to Work” for the past four years in a row. 

Learn more at www.AKASA.com.  

We are building the future of healthcare with AI. Everyone is welcome. As an inclusive workplace, we are committed to building an environment where our employees are comfortable bringing their authentic selves to work.  

Join us!

About the Role 

As a remote Sr. Software Engineer, on the Core Platform team, you will work on Medical Coding. You will work closely with the product, design, and machine learning teams to design and build services, APIs, and tools that support our internal applications and external SaaS products. 

You will create and maintain backend services and deploy machine learning at scale to solve challenging problems in healthcare such as automated medical coding and document selection.  You will be responsible for developing and supporting processing pipelines involving multiple internal and external machine learning and large language models, as well as custom algorithms interpreting structured and unstructured medical information.  You will productionize models developed and trained by our ML team and troubleshoot issues.  These models, together with purpose-built user interfaces, will accelerate the work of highly trained medical professionals responsible for handling millions of dollars of hospital revenue. 

You will be expected to come up with creative solutions, share your experience with the team, communicate complex technical concepts to less technical users, help mentor junior team members, and work together to shape the platform architecture.
AKASA is based in South San Francisco. As a company, we embraced remote work. We consider ourselves experts in working collaboratively wherever our team members reside.

What You'll Do

• Partner closely with our product, design, and machine learning teams

• Design, build, and maintain shared APIs, tools, services, and applications

• Lead and participate in design discussions, planning sessions, and code reviews.

• Debug issues and support customers

• Mentor junior engineers on the team

• Work with team members to shape AKASA’s platform architecture

Skills & Qualifications

• Bachelor of Science in Computer Science/Software Engineering or related field.

• 5+ years of work experience in software development, data engineering or machine learning.

• Significant experience deploying a trained system to production (recommendation, classification or similar features).

• Backend web/web services experience with schema design and API implementation focus in a distributed environment.

• Strong concurrent/parallel/asynchronous programming skills in Python.

• Familiarity with FastAPI, SQLAlchemy, Postgres.

• Strong communication and interpersonal skills with meticulous attention to detail

Nice to haves

• Experience with PyTorch, Keras or other machine learning frameworks a plus.

• Prompt engineering experience.

• Proficiency in Docker, Kubernetes, AWS.

• CI/CD experience with GitHub Actions.

• Firm grasp of system design principles.

• Knowledge of AI/ML, particularly generative AI.

• Experi