Machine Learning Engineer II (AI)

TL;DR

Machine Learning Engineer II (AI): Building and optimizing AI/ML solutions to improve healthcare revenue cycle processes with an accent on Natural Language Processing, MLOps practices, and scalable model deployment. Focus on designing experiments to test architectures, monitoring models in production, and maintaining complex data pipelines from raw sources to feature stores.

Location: 100% remote within the United States. Must be able to use a camera for all virtual meetings.

Salary: $108,638 - $135,000 per year

Company

hirify.global delivers revenue cycle and related business solutions for health care professionals, providing tools, insights, and network reach to thrive in a changing industry.

What you will do

• Support the goal of connecting providers, payers, and patients to the Internet of Healthcare.
• Utilize NLP and AI/ML toolkits to build solutions for improving prior authorization.
• Design experiments to test machine learning architectures and deploy selected models as service endpoints.
• Monitor models in production, update them for performance improvement, and automate processes.
• Understand and maintain data pipelines from raw sources to feature stores for models.
• Communicate project status and blockers within the team, adhering to security and data protection policies.

Requirements

• Master’s degree in Data Science, Data Analytics, Business Analytics, Information Systems, or a directly related field, plus 3 years of experience as a data scientist or machine learning engineer.
• 2 years of experience with: designing and deploying end-to-end regression and classification models on AWS SageMaker; Databricks using scikit-learn and PySpark ML (including techniques for handling highly imbalanced datasets); Natural Language Processing; Hugging-Face with PyTorch to process unstructured text and generate dense embeddings.
• 2 years of experience with: healthcare data standards (EDI 835/837 and medical coding systems like ICD-10, CPT, HCPCS, SNOMED-CT), and secure handling of PHI and PII.
• 1 year of experience with: developing and deploying RESTful web APIs for ML model inference using FastAPI, Flask, and Django frameworks; Docker containerization to create reproducible and scalable environments for ML models and cloud-native deployment using Amazon ECS and EKS; writing queries using PySpark on Databricks to retrieve and process semi-structured data.
• Must be authorized to work in the United States and comply with I-9 and E-Verify requirements.
• Must pass a drug test before beginning employment.

Culture & Benefits

• Fosters a collaborative and open culture, operating as a remote-first company.
• Requires camera usage for all virtual meetings to enhance connection and security.
• Provides powerful tools, actionable insights, and an expansive network.
• Committed to being an equal opportunity employer and a drug-free workplace.