We are seeking a Lead AI/ML Engineer to drive the migration of patient predictive models into a new analytical rework framework, architect scalable ML solutions on AWS, and lead the implementation of agentic workflows powered by GenAI and LLM capabilities. This role combines hands-on technical leadership with team enablement, guiding the transition of critical healthcare models while ensuring data integrity, operational continuity, and adoption across the organization.

Responsibilities

Design and develop the migration solution for existing patient predictive models into the new analytical rework framework
Architect the model transition approach to ensure data integrity and prediction accuracy
Implement MLOps practices for model lifecycle management and monitoring
Execute the transition of all in-scope patient models to AWS-native ML services
Validate migrated models against baseline performance metrics
Ensure operational continuity throughout the migration process
Design and implement agentic and multi-agent workflow patterns




Integrate GenAI and LLM capabilities into the analytical framework
Develop automation for model training, evaluation, and deployment pipelines
Lead team onboarding sessions for the new analytical framework
Conduct comprehensive knowledge transfer sessions to support adoption
Create documentation and training materials for operational handoff

Requirements

5+ years of experience in AI/ML engineering with strong expertise in Amazon Web Services (AWS)
Deep background in data engineering
Extensive skills in MLOps
Strong qualifications in agentic workflows and multi-agent systems
Solid expertise in Large Language Models (LLM) and GenAI
High proficiency in Python
English proficiency at B2 level or higher

Nice to have

Familiarity with Amazon SageMaker
Familiarity with AWS Bedrock
Background in healthcare domain
Experience in patient data analytics and predictive modeling

We offer

International projects with top brands
Work with integral teams of

📌 Lead AI/ML Engineer (Argentina)
🏢 EPAM Systems
📍 Argentina