AI/ML DevOps Engineer (In-Person Interview)

Position: AI/ML DevOps 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