Posted:1 week ago|
Platform:
Remote
Contractual
Job Title: MLOps Architect Experience: 10+ Years Location: Remote Type-Contractual About the Role: We are seeking experienced MLOps Engineers to join our growing team of AI/ML professionals. The ideal candidate will have deep experience in machine learning deployment pipelines , infrastructure automation , and monitoring , with a passion for building scalable and reliable systems. This is a remote full-time opportunity with a competitive compensation package. Key Responsibilities: Design, develop, and maintain robust CI/CD pipelines for deploying machine learning models into production. Package and deploy models built with TensorFlow or PyTorch using Azure ML , AWS SageMaker , or GCP Vertex AI . Automate containerization using Docker , and manage deployment using Kubernetes (preferred). Collaborate with data scientists and engineers to streamline model training, evaluation, and deployment workflows. Implement monitoring and alerting systems using tools such as Prometheus , Grafana , and Azure Monitor . Ensure system reliability, availability, and performance optimization across environments. Maintain and manage version control using Git and CI/CD pipelines using GitLab CI/CD or equivalent. Work in a Linux environment, writing scripts to automate deployment, logging, and maintenance tasks. Required Skills: Strong hands-on experience with Docker , CI/CD pipelines , and Linux-based deployments . Experience with cloud platforms: Azure ML (preferred), AWS , or GCP . Proficiency in Python scripting and automation. Familiarity with ML model deployment pipelines and infrastructure as code. Experience with monitoring tools like Grafana , Prometheus , and Cloud-native logging/alerting systems . Working knowledge of Kubernetes (preferred). Ideal Candidate Profile: 6+ years of experience in MLOps, DevOps , or related backend infrastructure roles. Proven experience in deploying TensorFlow/PyTorch models in production environments using Azure ML and GitLab CI/CD . Demonstrated expertise in monitoring , alerting , and performance tuning of ML systems. Strong problem-solving, communication, and documentation skills. Show more Show less
MindBrain Foundation
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Salary: Not disclosed
Salary: Not disclosed
