technical
MLOps Engineer
MLOps Engineers build the infrastructure and pipelines that take ML models from research to production. You'll manage model versioning, build CI/CD pipelines for ML, monitor model performance in production, and ensure reliable scaling. The DevOps equivalent for machine learning teams.
$120k – $240k
Very High Demand
Moderate Competition
A Day in the Life
MorningCheck model serving dashboards, investigate latency spikes
MiddayBuild automated retraining pipeline, update model registry
AfternoonOptimize GPU utilization, review infrastructure costs
EveningSet up A/B testing framework for new model version, write runbooks
Key Skills
Docker / KubernetesEssential
ML Pipeline Tools (Kubeflow, Airflow)Essential
Model Serving (TensorRT, Triton)Essential
Monitoring & ObservabilityImportant
Python / BashImportant
Cloud Platforms (AWS, GCP)Helpful
CI/CD for MLHelpful
Career Growth Path
Junior MLOps
MLOps Engineer
Senior MLOps
ML Platform Lead
Director of ML Infrastructure
Ideal Personality Traits
SystematicReliableDetail-orientedPragmaticCollaborative
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