Senior MLOps Engineer: Build a Self-Serve ML Platform

Veridic Solutions LLC; Austin (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

Veridic Solutions LLC seeks a Senior MLOps Engineer to design and deliver a next‑generation ML Platform‑as‑a‑Product. You will abstract infrastructure complexities so ML engineers and data scientists can write, train, deploy, and monitor models in production.

Responsibilities cover standardizing development environments, building scalable training pipelines with Vertex AI, Kubeflow, and Databricks, and implementing end‑to‑end observability with automated retrain loops on GKE/Vertex Endpoints.

Qualifications

• Experience building a unified ML Platform-as-a-Service for internal engineering use.
• Strong knowledge of MLOps, CI/CD for ML, automated testing, and canary deployments.

Responsibilities

• Architect and build an end-to-end ML Platform-as-a-Product.
• Standardize notebooks, local CLI tools, and SDKs for repeatable model development.
• Develop scalable training pipelines using Vertex AI Pipelines, Kubeflow, and Databricks.
• Create CI/CD/CT pipelines to package models into scalable microservices on GKE or Vertex Endpoints.
• Implement observability, data/concept drift monitoring, and automated retrain triggers.
• Manage enterprise Feature Store, artifact registries, and metadata lineage.

Skills

Platform architecture

CI/CD

ML GItOps

Monitoring & observability

Tools

Vertex AI

GKE

Kubeflow

Databricks

Terraform

BigQuery

Google Cloud Storage

Job description

Veridic Solutions LLC seeks a Senior MLOps Engineer to design and deliver a next‑generation ML Platform‑as‑a‑Product. You will abstract infrastructure complexities so ML engineers and data scientists can write, train, deploy, and monitor models in production.

Responsibilities cover standardizing development environments, building scalable training pipelines with Vertex AI, Kubeflow, and Databricks, and implementing end‑to‑end observability with automated retrain loops on GKE/Vertex Endpoints.