Senior Machine Learning Engineer (MLE)
Location: Remote - USA (Alabama, Arkansas, Delaware, Florida, Georgia, Iowa, Illinois, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Maine, Maryland, Michigan, Minnesota, Missouri, Mississippi, Montana, North Carolina, Nebraska, New Hampshire, Ohio, Oklahoma, Pennsylvania, Rhode Island, South Carolina, Tennessee, Texas, Virginia, Wisconsin, West Virginia)
Company Overview:
My client is a leading private equity-backed organization that specializes in recovering healthcare costs on behalf of hospitals across the United States. The company handles an enormous volume of unresolved claims each year, with a mission to recover significant revenue that enhances hospital operations. By leveraging advanced AI/ML techniques, my client is transforming the way healthcare claims are processed, ensuring more efficient and successful recovery outcomes.
Position Overview:
My client is seeking a Senior Machine Learning Engineer (MLE) to join their dynamic team, focusing on developing and optimizing machine learning models that improve the efficiency and accuracy of healthcare claim processing. In this role, you will work closely with a team of data scientists and engineers to implement models that prioritize and flag claims, ensuring the right resources are allocated to the most impactful tasks. This is a critical position that will help drive the company’s mission to maximize revenue recovery for healthcare providers.
Key Responsibilities:
- Develop and refine machine learning models to improve claim recommendations, staffing efficiency, and claim exploration processes.
- Work with messy and evolving datasets, continually adapting models to accommodate new data and changing client needs.
- Collaborate with the engineering team to ensure that ML models are robust, scalable, and fully integrated into production systems.
- Focus on model improvements, particularly in recommendation systems, to enhance the accuracy and efficiency of claim processing.
- Engage in the full machine learning lifecycle, from data preprocessing to model deployment and monitoring.
- Work with a multidisciplinary team to prioritize rules and claims, improving operational efficiency and increasing revenue.
Qualifications:
- 4+ years of experience in machine learning engineering or a related field, with a focus on complex data environments.
- Strong engineering skills with an emphasis on handling messy, evolving datasets.
- Attention to detail and a passion for continuous improvement in model performance.
- Experience in recommendation systems and MLOps is highly desirable.
- Ability to work in industries with complex data, such as insurance, fraud detection, e-commerce, loans, or consulting.
- Prior experience in healthcare is a plus, but not required.
Compensation:
- Competitive salary up to $200,000, plus a 10% bonus.
- Opportunities for professional growth and development within a forward-thinking organization.
Application Process:
- Initial screening with the hiring manager.
- Technical screening.
- Virtual onsite interviews.
If you are a skilled machine learning engineer with a passion for leveraging AI to solve real-world problems, my client would love to connect with you. Apply today to be part of a team that is transforming healthcare claims processing through innovative machine learning solutions.
