MLOps Engineer role guide
MLOps Engineer careers in the United States: responsibilities, stack (mlops, mlflow, kubeflow, pipeline), training paths, salaries, and 16 active job listings on Ganloss.
MLOps Engineer is a core profile on the US artificial intelligence job market. Ganloss currently lists 16 open roles for this profile. This page covers day-to-day work, skills, typical career paths, and resources for applying in 2026.
Day-to-day responsibilities
Model CI/CD, orchestration (Airflow, Kubeflow), feature stores, drift monitoring, version and GPU environment management. Bridge between data science and SRE.
Stack & skills employers want
Kubernetes, Docker, Terraform, MLflow, Python, cloud (AWS/GCP/Azure), observability, IaC, DevOps practices.
Typical career path
Scarce, well-paid profile. Often ex–data engineer or ex–ML engineer. High demand where companies move from POC to production AI.
Cross-functional skills
Market keywords: mlops, mlflow, kubeflow, pipeline, feature store. Strong communication, experimentation discipline, product sense, and collaboration with business teams are expected on most MLOps Engineer roles.
Training & career switch
Common paths: CS/ML bachelor's or master's, accredited bootcamps, or self-taught portfolios with production projects. Browse LLM, ML, and MLOps training on Ganloss before you apply.
First steps to apply
1) Match your resume to MLOps keywords. 2) Document 2 production or POC projects. 3) Check salary guides for your target city. 4) Apply on Ganloss with your candidate profile.
Go further
FAQ
- How to become an MLOps engineer?
- Data engineer path plus ML in prod, or ML engineer leveling up on infra. Cloud certs and a documented pipeline portfolio help.
- Where to find MLOps Engineer jobs in the United States?
- Browse the MLOps Engineer job hub on Ganloss, filter by city or remote, and enable email alerts for new listings.
Related jobs
MLOps EngineerSalesforce 4.4 · 328 reviewsModel deployment and monitoring for Einstein platform services — Seattle hub.
MLOpsKubernetesPythonSeattleSeattle, WAHybrid$145k – $190k / yearEasy applyFull-time18 applicantsPosted 3 days agoQuick preview
ML Engineer — FoundryPalantir 4.4 · 262 reviewsProduction ML pipelines on Foundry for commercial enterprise AI deployments.
MLPythonMLOpsEnterpriseSan Francisco, CAHybrid$165k – $225k / yearEasy applyFull-time12 applicantsPosted 3 days agoQuick preview
MLOps EngineerDatabricks 4.5 · 180 reviewsMLOps engineer for mountain west SaaS customers — model registry, feature stores, and GPU scheduling.
MLOpsDenverSparkMLflowDenver, COHybrid$135k – $180k / yearEasy applyFull-time31 applicantsPosted 4 days agoQuick preview
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