Hybrid MLOps Engineer — AI Cloud Platform Lead

Modernizing Medicine, Inc.; United States; Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Comprehensive medical, dental, and vis

401(k) matching

Tuition reimbursement

Job summary

Modernizing Medicine, Inc. is seeking a Staff MLOps Engineer to bridge data science, ML engineering, and production systems.

You will establish architecture and tooling for fast, reliable, and secure AI‑enabled applications at scale, shaping model training, deployment, and lifecycle management. You will implement CI/CD, IaC, and observability, work with Data Science, Security, and Product teams, mentor MLOps engineers, and help advance secure, cost‑efficient AI capabilities across our enterprise

Qualifications

• 8+ years of experience in DevOps, MLOps, Software Engineering, or Cloud Architecture.
• Proficient in Python and production‑grade microservices.
• Experience with 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.

Responsibilities

• Architect and operate a scalable platform to deploy AI/ML models into high‑throughput production applications.
• Define reusable patterns for model training, feature store integration, batch/real‑time inference, and pipelines.
• Ensure IaC‑driven, multi‑environment deployments across AWS accounts.
• Lead the evolution of serverless and containerized ML execution environments, migrating pipelines to Kubernetes microservices where applicable.
• Drive CI/CD and GitOps for automated model delivery and infrastructure‑as‑code automation.
• Design comprehensive observability and monitoring using DataDog to track drift, latency, errors, and health in production.
• Implement LLMOps and AIOps frameworks to manage, deploy, evaluate, and monitor LLMs and generative AI solutions, leveraging MLflow.
• Partner with Data Science, Product Development, and Security teams to ensure models are secure, compliant, and cost‑efficient.
• Provide technical leadership and mentorship across MLOps and engineering teams, codifying best practices in system architecture.

Skills

Python

DevOps/MLOps

Kubernetes/EKS

AWS

CI/CD/GitOps

Serverless (Lambda)

DataDog observability

ML lifecycle architecture

Leadership

Tools

MLflow

SageMaker

PyTorch

Spark

Databricks

Terraform

Job description

Modernizing Medicine, Inc. is seeking a Staff MLOps Engineer to bridge data science, ML engineering, and production systems.

You will establish architecture and tooling for fast, reliable, and secure AI‑enabled applications at scale, shaping model training, deployment, and lifecycle management. You will implement CI/CD, IaC, and observability, work with Data Science, Security, and Product teams, mentor MLOps engineers, and help advance secure, cost‑efficient AI capabilities across our enterprise