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MLOps Engineer — Model Deployment & Monitoring

Synaptic Labs

Remote · $80 – $120 / hour · Freelance · Posted 9 months ago

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About the role

We need an experienced MLOps engineer for a 6-month engagement to help us migrate our ML model serving from a manual notebook-based workflow to a fully automated, monitored pipeline. Currently: models are deployed manually, there is no drift monitoring, and retraining is done ad hoc. Goal: CI/CD for models, automated retraining triggers, drift alerts, and a clean deployment process on AWS. You won't be building models — you'll be building the infrastructure that makes our models reliable and reproducible.

Fully remote.

Requirements

Technical stack needed for this mission.

  • – Strong Kubernetes and Docker experience
  • – Experience with MLflow or similar experiment tracking
  • – AWS (SageMaker, EKS, or Lambda) deployment experience
  • – Has set up CI/CD pipelines for ML models before
  • – Can work EU timezone hours

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Categories

MLOps & AI Infrastructure

Skills

docker kubernetes mlflow airflow aws

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Contract Type

Hourly rate

Level

Senior

Budget Range

$80 – $120 / hour

Duration

6 months

AI Expertise

MLOps & AI Infrastructure MLOps & Industrialisation

Skills

docker kubernetes mlflow airflow aws ci/cd python

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About Synaptic Labs

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