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Staff MLOps Engineer - Clinical Documentation AI

James Okafor

Full-time · Senior · New_York

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About the role

We build software used by clinical operations teams to review, summarise, and route visit documentation. The models are important, but reliability is what determines whether hospitals trust the product. This role sits between platform engineering and applied ML. You would own deployment standards, model release safety, and production diagnostics for a stack that cannot afford guesswork.

Responsibilities

  • Own the deployment patterns used by NLP and document intelligence services
  • Improve rollback, monitoring, and incident triage for production model releases
  • Partner with security and compliance teams on deployment controls
  • Reduce operational toil across training-to-serving handoffs
  • Coach engineers on production readiness for new AI features

Requirements

  • 7+ years in platform, MLOps, or infrastructure engineering
  • Kubernetes and Docker in production environments
  • AWS services such as EKS, IAM, S3, and CloudWatch
  • MLflow or similar tooling for model tracking and release governance
  • CI/CD ownership for infrastructure and model-serving workflows
  • Python for automation, debugging, and internal tooling

Benefits

  • $155,000 - $182,000 base salary
  • Remote in the US with quarterly meetups
  • Equity grant and annual performance bonus
  • Robust health coverage for family plans
  • A product environment where reliability matters every day

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Categories

MLOps & AI Infrastructure

Skills

python kubernetes aws mlflow ci/cd

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$155,000 - $182,000

AI Expertise

MLOps & AI Infrastructure

Skills

python kubernetes aws mlflow ci/cd

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