h3 Technologies, LLC

MLOps Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOps Engineer in Scottsdale, AZ, on a long-term contract. Pay rate is W2/1099. Requires 5+ years in DevOps/ML Ops, expertise in GCP/AWS ML services, containerization, and proficiency in Python. Preferred certifications include Google Cloud Professional Machine Learning Engineer or AWS Certified Machine Learning – Specialty.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
October 11, 2025
🕒 - Duration
Unknown
-
🏝️ - Location
On-site
-
📄 - Contract
W2 Contractor
-
🔒 - Security
Unknown
-
📍 - Location detailed
Scottsdale, AZ
-
🧠 - Skills detailed
#GCP (Google Cloud Platform) #Terraform #AWS (Amazon Web Services) #Cloud #Jenkins #Data Engineering #AWS SageMaker #DevOps #Docker #GitHub #PyTorch #Kubernetes #AI (Artificial Intelligence) #ML Ops (Machine Learning Operations) #Bash #GitLab #Python #SageMaker #TensorFlow #Scala #Programming #Data Ingestion #BigQuery #Deployment #Data Science #ML (Machine Learning) #Monitoring
Role description
NO C2C- W2/1099 USC/GC Locals to AZ This is not a devops engineer role so kindly read the JD before applying Position: MLOps Engineer Location: Scottsdale, AZ must sit and need to go in for an in-person interview. Terms: Long Term Contract We are seeking a highly skilled AIML DevOps Engineer to join our growing team. You will work closely with DevOps engineers, data scientists, ML engineers, and software developers to build, deploy, and scale machine learning models and AI-driven applications in production environments. Key Responsibilities: • Design, implement, and maintain ML pipelines for training, testing, and deploying AI/ML models. • Manage and optimize cloud-based ML infrastructure (GCP Vertex AI, AWS SageMaker, or equivalent). • Implement CI/CD pipelines for ML and AI-driven applications. • Monitor, troubleshoot, and optimize model performance and system reliability. • Automate workflows for data ingestion, model training, deployment, and monitoring. • Collaborate with cross-functional teams to ensure secure, scalable, and compliant ML operations. • Apply MLOps best practices for reproducibility, versioning, and governance of ML models. Required Qualifications: • 5+ years' experience in DevOps, CloudOps, or ML Ops. • 5+ years' experience with GCP AI/ML services (Vertex AI, AI Platform, BigQuery ML) or AWS ML services (SageMaker etc) • 5+ years' Experience with containerization and orchestration (Docker, Kubernetes). • Proficiency in infrastructure-as-code (Terraform, CloudFormation, or Deployment Manager). • Familiarity with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, or ArgoCD). • Strong programming skills in Python, Bash, or Go, with experience in ML frameworks (TensorFlow, PyTorch, Scikit-learn). Preferred Certifications (one or more) • Google Cloud Professional Machine Learning Engineer • Google Cloud Professional Data Engineer • AWS Certified Machine Learning – Specialty • Certified Kubernetes Admin(CKA) • Google Professional Cloud Architect Best Regards, Grace Abinezer Recruitment Consultant | H3 Technologies, LLC 📞 (859) 287-0731 📧 grace@h3-staffing.com 🌐 www.h3-technologies.com 71 Cavalier Blvd., Suite 208, Florence, KY - 41042 linkedin.com/in/grace-ebenezer-bb66a0251