MLOps Engineer - Independent Contractors

Title: MLOps Engineer Location: Grapevine, TX (Dallas, TX) - hybrid onsite Required Skills & Experience Core Requirements (Must Have) • Proven experience owning MLOps lifecycle end-to-end in production environments • Strong Python engineering experience (building scalable services, pipelines) • Hands-on expertise with CI/CD pipelines for ML systems • Experience supporting multiple ML products or platforms simultaneously MLOps & ML Tooling Deep knowledge of: • MLflow / Kubeflow (or similar orchestration frameworks) • Model versioning, experiment tracking, and pipeline orchestration • Data monitoring, drift detection, and model observability Strong understanding of machine learning fundamentals and lifecycle management Data & Cloud Ecosystem Experience with: • GCP (preferred), Azure, or hybrid environments • Big Data ecosystems (Databricks, Spark, distributed processing) • SQL and large-scale data pipeline development • Familiarity with cloud-based ML infrastructure and scaling strategies Engineering & Systems Proficiency in: • Shell scripting and automation • Containerization and orchestration (Docker, Kubernetes) • Building reliable, scalable backend systems for ML inference