MLOps Engineer

Role : MLOps Engineer Location : Dallas TX(Onsite) Experience: 8+ yearsType : C2C and W2 both We are seeking an MLOps Engineer to bridge the gap between data science and production systems, ensuring that machine learning models are deployed, monitored, and maintained at scale. You will work closely with data scientists, data engineers, and software developers to design and implement automated, reliable, and secure ML pipelines from development to production. Key Responsibilities Model Deployment & Serving Deploy ML models into production environments using tools such as Docker, Kubernetes, and model serving frameworks (e.g., TensorFlow Serving, TorchServe, MLflow). Implement CI/CD pipelines for ML workflows. Pipeline Development & Automation Build and maintain end-to-end machine learning pipelines for data ingestion, preprocessing, training, validation, deployment, and monitoring. Automate model retraining and versioning to ensure continuous improvement. Monitoring & Maintenance Set up monitoring and alerting systems for model performance, data drift, and infrastructure health. Troubleshoot and resolve model degradation issues in production. Collaboration & Integration Collaborate with data scientists to transition models from experimentation to production-ready systems. Work with DevOps and cloud teams to ensure ML workloads are scalable and cost-efficient. Security & Compliance Ensure compliance with data governance, security, and privacy regulations. Manage role-based access control (RBAC) for ML infrastructure. Job Types: Part-time, Contract Pay: $65.00 - $75.00 per hour Work Location: In person