Join the Team Modernizing Medicine
At ModMed , we’re not just building software—we’re reimagining the healthcare experience. Founded in 2010 by a practicing physician and a successful tech entrepreneur, we took a radically different approach: we hired doctors and taught them how to code. This "for doctors, by doctors" philosophy has allowed us to create an AI-enabled, specialty-specific cloud platform that places patients at the center of care.
A Culture of Excellence
When you join ModMed, you’re joining an award-winning team recognized for innovation and employee satisfaction. From our global headquarters in Boca Raton Florida, and extensive employee base in Hyderabad India, we are a team of 4,500+ passionate problem-solvers on a mission to increase medical practice success and improve patient outcomes:
Consistently ranked as a Top Place to Work
2025 Globee Business Awards: Gold Globee for “Technology Team of the Year”
2025 Black Book Awards: Ranked #1 EHR in 11 Specialties
Florida Venture Forum: Venture-Backed Company of the Year
We are growing fast, thinking big, and we are just getting started.
Ready to modernize medicine with us?
Job Description Summary:
As a Staff MLOps Engineer at Modernizing Medicine, you’ll help bridge the gap between data science, machine learning engineering, and production systems. You’ll lead efforts to establish architecture and tooling that make it fast, reliable, and secure for our developers to build, deploy, and operate AI-enabled applications at scale. You will drive core architectural patterns for model training, deployment, and lifecycle management, empowering self-service capabilities across product and platform teams. Your work will directly shape the enterprise platform driving our next generation of AI-driven clinical and operational products.
What You’ll Do
Architect and help build and operate a scalable developer enablement platform for deploying AI/ML models into high-throughput production applications, accelerating the end-to-end lifecycle of AI-enabled applications.
Define reusable patterns for model training, feature store integration, batch/real-time inference, and pipeline orchestration using Databricks, Airflow, and cloud-native services.
Ensure ML infrastructure is built on standardized IaC to ensure repeatable, multi-environment deployments across AWS accounts.
Lead the evolution of serverless and containerized ML execution environments, migrating high-scale serverless pipelines (AWS Lambda) to Kubernetes (EKS) microservices where appropriate.
Drive CI/CD and GitOps standards for automated model delivery, champion deployment strategies, and infrastructure-as-code automation.
Design comprehensive observability and monitoring capabilities using DataDog to track model drift, latency, error rates, and system health in production.
Implement LLMOps and AIOps frameworks to manage, deploy, evaluate, and monitor Large Language Models (LLMs) and generative AI solutions, leveraging MLflow for tracking, experiment management, and model registry.
Partner closely with Data Science, Product Development, and Security teams to ensure models and AI applications are secure, compliant, and cost-efficient.
Apply security best practices to protect sensitive data and ensure compliance.
Provide technical leadership and mentorship across MLOps and engineering teams, codifying best practices in system architecture and operational excellence.
What We’re Looking For
8+ years of experience in DevOps, MLOps, Software Engineering, or Cloud Architecture with proven experience delivering and operating AI/ML systems at scale.
Deep expertise in Python and software engineering principles for production-grade microservices, SDKs, and data pipelines.
Proven architectural experience with patterns across the full ML lifecycle: training, batch/real-time inference, model registration, and application integration.
Strong proficiency with container orchestration (Kubernetes/EKS), serverless architectures…