We are an AI-driven company focused on building innovative tools for detecting and verifying fake news. Our platform uses advanced machine learning algorithms, including Graph Neural Networks, BERT-based sentiment analysis, LDA for topic modeling, and cutting-edge techniques to analyze and verify news articles and social media posts. We aim to combat misinformation and promote truth in the digital world. We are looking for a highly skilled DevOps/MLOps Engineer with experience in cloud infrastructure, specifically Azure, to join our growing team. If you are passionate about AI, news verification, and developing robust infrastructure solutions for large-scale machine learning systems, we want to hear from you!
Responsibilities:
- MLOps Pipeline Development: Design, implement, and maintain scalable machine learning pipelines on Azure to support model training, testing, and deployment.
- Cloud Infrastructure: Manage and optimize our Azure-based infrastructure, ensuring the reliability, scalability, and security of our AI tool.
- Automation & CI/CD: Set up continuous integration/continuous deployment (CI/CD) pipelines for both traditional software and machine learning models to streamline releases.
- Monitoring & Performance: Implement monitoring and alerting systems to track model and system performance, ensuring high availability and quick response to any issues.
- Security & Compliance: Ensure security best practices are followed and that systems comply with industry standards and regulations, especially concerning data privacy.
- Model Deployment: Deploy and manage machine learning models in production, monitor model drift, and ensure robust version control.
- Infrastructure as Code (IaC): Use tools like Terraform, Azure Resource Manager (ARM), or similar to manage infrastructure through code.
Requirements:
Experience with Azure: Proven experience working with Azure services, including Azure Machine Learning, Azure Kubernetes Service (AKS), Azure Data Lake, and Azure DevOps. DevOps/MLOps
Expertise: Hands-on experience in building and managing CI/CD pipelines, container orchestration (e.g., Docker, Kubernetes), and automation for machine learning workflows.
Cloud Infrastructure: Experience in managing cloud-based infrastructure, optimizing costs, and ensuring high availability and security.
Monitoring & Logging: Familiarity with monitoring tools such as Prometheus, Grafana, or Azure Monitor for system and application performance tracking.
ML Model Deployment: Experience in deploying machine learning models into production environments and managing them over time.
Problem-Solving Skills: Ability to troubleshoot complex issues across multiple systems and find creative solutions to technical challenges.
Preferred Skills:
- Experience with Terraform or Azure Resource Manager for infrastructure as code.
- Experience with large-scale data pipelines and data engineering workflows.
- Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Experience working with AI-based projects, particularly in news verification or misinformation detection.
Benefits:
Opportunity to work on cutting-edge AI technologies.
Collaborate with a passionate and driven team working to combat misinformation in a dynamic startup.
Equity and other perks