Staff Cloud Engineer, ML Ops

Modernizing Medicine; Boca Raton (FL); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Comprehensive benefits

Job summary

Modernizing Medicine is seeking a Staff MLOps Engineer to bridge data science, machine learning engineering, and production systems. You will lead architecture and tooling for fast, reliable, and secure AI-enabled applications at scale, empowering self-service capabilities for product and platform teams.

You will drive model training, deployment, and lifecycle management, partnering with Data Science, Product, and Security to ensure secure, compliant, and cost-efficient solutions.

Qualifications

• 8+ years of experience in DevOps, MLOps, Software Engineering, or Cloud Architecture.
• Strong Python and production-grade software engineering skills.
• Experience with Kubernetes/EKS, Lambda, and AWS infrastructure.
• Experience with MLflow, SageMaker, PyTorch, or Spark; Databricks a plus.

Responsibilities

• Architect and operate a scalable developer enablement platform for deploying AI/ML models into production applications.
• Define reusable patterns for model training, feature store integration, inference, and pipelines using Databricks, Airflow, and cloud services.
• Ensure ML infrastructure uses IaC for repeatable deployments across AWS accounts.
• Lead evolution of serverless and containerized ML execution environments; migrate Lambda-based pipelines to Kubernetes where appropriate.
• Drive CI/CD and GitOps standards for automated model delivery and infra automation.
• Design observability and monitoring with DataDog to track model drift, latency, and health.

Skills

Python

Microservices

Kubernetes

AWS

MLflow

SageMaker

PyTorch

Terraform

CI/CD

DataDog

Leadership

Job description

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.

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 (Lambda), and cloud infrastructure (AWS).


• Hands‑on experience with ML and LLM frameworks such as MLflow, SageMaker, PyTorch, or Spark; experience with Databricks is a plus.


• Mastery of Infrastructure as Code (Terraform) and CI/CD/GitOps tooling.


• Demonstrated capability in establishing enterprise observability standards using DataDog or similar platforms.


• Strong leadership, communication, and cross‑functional collaboration skills with a focus on developer enablement and mentoring.

This role is hybrid. On-call participation may be required to support production systems.

If you're excited about bringing machine learning to life through clean code, automation, and infrastructure excellence, we want to talk.

ModMed Benefits Highlight:

At ModMed, we believe it's important to offer a competitive benefits package designed to meet the diverse needs of our growing workforce. Eligible Modernizers can enroll in a wide range of benefits:

United States

Comprehensive medical, dental, and vision ben