Staff Machine Learning Engineer
Angi- Full Time
- Expert & Leadership (9+ years)
Candidates should have a strong background in machine learning and engineering, with experience in managing engineering teams. A proven track record in deploying machine learning models in production environments is essential. Familiarity with large language models (LLMs) and experience in developing infrastructure for model development are required.
The Sr. Engineering Manager will lead a team of engineers to enhance AKASA’s machine learning capabilities and deliver innovative products. They will supervise and contribute to all aspects of the LLM stack, including model fine-tuning, inference, evaluation, and deployment. Additionally, they will develop infrastructure and tooling to streamline the model development lifecycle.
Automates revenue cycle management processes
AKASA offers technology solutions that enhance efficiency and revenue outcomes for healthcare organizations by using a mix of computer vision-based Robotic Process Automation (RPA), machine learning, and human-in-the-loop automation. Their services streamline complex Revenue Cycle Management (RCM) workflows, allowing healthcare staff to focus on more meaningful tasks. Unlike competitors, AKASA specifically targets operational inefficiencies in revenue cycle departments, helping clients like Methodist Health System achieve significant gross yield increases. The company's goal is to empower healthcare organizations to improve their operational efficiency and patient experience.