Senior MLOps Engineer, Intapp

• 5+ years of technical experience in a SaaS company
• 3+ years of experience in Infrastructure, DevOps, or MLOps
• Expertise in cloud platforms (e.g., Microsoft Azure), containerization technologies (Docker, Kubernetes), and CI/CD tools (ArgoCD, Azure DevOps, Helm)
• Ability to design scalable, secure, and efficient cloud systems, and familiarity with security and compliance standards in enterprise-grade cloud environments
• Preference given to anyone that has experience deploying or managing ML systems in production, are familiar with machine learning concepts and have interest in AI/ML

Desirable

• We're looking for a passionate Engineer to join our Cloud Engineering team and revolutionize how we develop and deploy AI models.
• You'll bridge the gap between data science and operations, ensuring our groundbreaking projects in ML, traditional AI, and Generative AI go from concept to reality
• Collaborate with multiple product teams to implement Security, Data Protection and MLOps strategies that fuel business growth and ensure High Availability for AI/ML workloads
• Implement and manage Continuous Deployment (CD) pipelines using tools such as ArgoCD and Helm
• Ensure compliance with security standards and architect and deploy scalable enterprise-grade cloud infrastructure for ML workloads using industry standard tools like Kubernetes
• Develop and maintain Infrastructure as Code (IaC) using tools like Terraform
• Implement robust model performance, cost, drift monitoring, and logging practices with tools like Prometheus, Langfuse, etc
• Build and automate end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring
• Champion MLOps best practices across the organization, mentoring and training stakeholders on tools and methodologies