MLOps engineers evaluated on ML pipelines, Kubernetes rollouts, and production monitoring — not DevOps buzzwords.
16 matching full-time / mid-level+ listings
Model deployment and monitoring for Einstein platform services — Seattle hub.
Production ML pipelines on Foundry for commercial enterprise AI deployments.
MLOps engineer for mountain west SaaS customers — model registry, feature stores, and GPU scheduling.
MLOps platform engineer — deploy and monitor eval pipelines for enterprise GenAI customers in the Southeast.
MLOps engineer for Midwest enterprise customers — hire MLOps engineers to run model CI/CD and monitoring at scale.
Junior ML engineer on generative video models — training pipelines, evals, and dataset tooling for creative AI products.
Automate model delivery pipelines for defense AI programs.
Operate private cloud and VPC deployments for regulated customers.
Guide healthcare and life-science customers on GPU-accelerated AI deployments.
Train and deploy models that block fraud at payment scale with low false positives.
Embed with public-sector customers to deliver mission-critical AI systems.
Design benchmarks and human-in-the-loop eval pipelines for frontier model customers.
Generic résumés do not prove production ability. Ganloss evaluates mlops engineers on ML CI/CD pipelines, feature stores, and monitored models in production — not keyword-stuffed skill lists.
Filter by stack, review GitHub, papers, or technical cases, then contact profiles with demonstrated level in the United States. $36/month — no hire commission.
Agencies charge 15–25% of annual salary and often recycle the same LinkedIn profiles. Ganloss combines a niche AI job board, tech talent pool, and project-based matching — hire faster with fewer mismatches.
Publish in about five minutes with Google for Jobs indexing and reach active candidates in the US AI market.