Machine Learning Engineer

About CORMAC

At CORMAC, we leverage the power of data management and analytics to enable our customers to achieve their strategic goals. With over 20 years of experience in health information technology (HIT), human-centered design principles, and Agile development methodologies, CORMAC delivers complex digital solutions to solve some of the most challenging problems facing public healthcare programs today.

As a US Federal Government contractor in the public healthcare sector, our work is impactful and cutting-edge while being performed in a supportive, collaborative, and welcoming environment. We offer flexible work schedules with remote, hybrid, or fully in-person workplace options to empower our employees to decide the workplace most suitable for them. At CORMAC, we have a highly diverse workforce and believe a work environment is a place where creativity, collaboration, enthusiasm, and innovation happen, regardless of location.

US Citizenship Required /E-Verify Participation/EEO

As an Equal Employment Opportunity employer, CORMAC provides equal employment opportunity to all employees and applicants without regard to an individual's protected status, including race/ethnicity, color, national origin, ancestry, religion, creed, age, gender, gender identity/expression, sexual orientation, marital status, parental status, including pregnancy, childbirth, or related conditions, disability, military service, veteran status, genetic information, or any other protected status.

Responsibilities

• Design, develop, train, validate, and deploy machine learning models to support predictive analytics, anomaly detection, classification, forecasting, and operational optimization
• Serve as the primary SME for machine learning strategy, architecture, and best practices across the program
• Build scalable ML pipelines using Databricks, Spark, Python, SQL, and cloud-native ML services
• Support use cases involving healthcare analytics, claims analysis, fraud detection, utilization forecasting, and operational performance improvement
• Collaborate with data architects, data engineers, business analysts, and stakeholders to translate business requirements into ML solutions
• Design and implement MLOps frameworks for model versioning, monitoring, retraining, CI/CD integration, and production deployment
• Optimize feature engineering, data preparation, model performance, and inference efficiency across large-scale datasets
• Establish model governance processes including explain ability, bias detection, validation, auditability, and compliance with federal and healthcare standards
• Support integration of ML outputs into online portals, reporting platforms, dashboards, and downstream operational systems
• Develop technical documentation, model design artifacts, and architecture recommendations for leadership and governance reviews
• Evaluate emerging AI/ML technologies and recommend modernization strategies aligned with CMS mission objectives
• Provide technical leadership, mentoring, and SME guidance to engineering and analytics teams

Required Skills & Experience

• Bachelor's degree in computer science/engineering related or equivalent degree
• 4+ years of experience in Information Technology (IT) and the software development lifecycle (SDLC)
• Strong experience building and deploying enterprise machine learning solutions in cloud environments
• Expertise in Python, SQL, Spark, ML frameworks (Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar)
• Experience with Databricks ML workflows, notebooks, feature engineering, and model deployment
• Strong understanding of MLOps, model lifecycle management, and production ML systems
• Knowledge of healthcare data analytics, data governance, and regulatory compliance considerations
• Experience with large-scale structured and unstructured datasets and distributed data processing
• Strong analytical, problem-solving, and stakeholder communication skills
• Ability to explain complex ML concepts to technical and non-technical audiences
• Experience supporting Centers for Medicare & Medicaid Services or other federal healthcare programs
• Familiarity with AWS Sage Maker, Azure ML, Snowflake, Tableau, Power BI, or Amazon QuickSight

Preferred Skills & Experience

• Master’s degree in Computer Science, Data Science, Machine Learning, Statistics, Engineering, or related field
• Certifications such as AWS Machine Learning Specialty, Databricks Machine Learning Associate/Professional, Azure AI Engineer, or related AI/ML certifications

Location

Leesburg, VA

Work Arrangement

100% Remote