Pre-vetted MLOps Engineer talent, fully managed delivery, structurally outcome-based pricing via Delivery Units. Onboarded in days — not months. No hiring overhead.
A MLOps Engineer pod from AiDOOS is a pre-assembled execution unit — vetted talent, a delivery manager, and the tooling to ship outcomes against your roadmap. We handle vetting, onboarding, governance, and reporting. You review shipped work against milestones.
MLOps Engineers at AiDOOS build the infrastructure and tooling that turns ML models into reliable production systems. Specialists cover model-deployment platforms (Sagemaker, Vertex AI, Databricks Model Serving, custom Kubernetes-based serving), feature stores (Feast, Tecton), model-monitoring (Arize, WhyLabs, custom), experimentation platforms, and CI/CD for ML specifically. Typical seniority: 5+ years with strong DevOps + ML background.
MLOps Engineers fit pods doing greenfield ML-platform builds, modernization of brittle ML-deployment processes, model-governance and compliance work for regulated industries, and platform-engineering work that scales ML capability across multiple model owners. The role overlaps with both ML Engineer (more model-focused) and Platform Engineer (more infrastructure-focused).
AiDOOS maintains a pre-vetted bench. Kickoff happens after scope alignment — not after a 60–90 day hiring funnel.
Every pod ships with a delivery manager, code-review SLAs, integration with your GitHub / Jira / Monday, and milestone reporting. Outcomes are auditable.
Add or release MLOps Engineer talent without long-term commitments. Delivery Unit (DU) pricing means you only pay for shipped, accepted work.
Pods are composed for the engagement. MLOps Engineers on AiDOOS pods commonly work across these technology stacks — pick the stack-specific page for engagement-fit details.
Pods include MLOps Engineers with prior sector experience. Each industry page covers compliance posture and common engagement types.
Tell us the outcomes you want shipped. We'll come back with a pod composition, milestone plan, and a pricing proposal — usually within 48 hours.