Machine Learning Engineer

Job Description

MLOps Engineer L3 As an MLOps Engineer, your day-to-day responsibilities will involve designing and managing machine learning operations pipelines using MLflow, Databricks ML Ops, and CI/CD pipelines. You will collaborate with data scientists to integrate machine learning models into production environments and automate model deployment and monitoring using Dataiku and other tools. Ensuring the scalability and reliability of machine learning workflows is crucial, and you will utilize Azure OpenAI and Argo CD for advanced automation and orchestration. Maintaining and optimizing cloud infrastructure for machine learning applications will be part of your daily tasks, along with monitoring the performance of machine learning models and workflows. Troubleshooting issues related to machine learning pipelines and infrastructure will be a regular part of your role, and you will maintain comprehensive documentation of processes, configurations, and best practices. Must-Have Skills: MLOps Tools: MLflow, Databricks ML Ops pipelines, CI/CD pipelines, Dataiku. Programming: Python, YAML scripting for pipeline automation. Terraform (highly recommended). Azure OpenAI. Argo CD (beginner). Azure Cloud proficiency: Azure Resource Management, AKS, ACS, Azure Functions, Azure Security. Azure Resources: Azure App services, Data Factory, and Azure Data Bricks (highly recommended). Networking: Network Security Groups, Virtual networks, Route Tables (highly recommended). Monitoring: Azure Monitor, Application Insights. Security: Azure Key Vault, RBAC, and secure CI/CD practices, IAM. Pluses: Azure ADO CI/CD pipelines. GitHub Actions. ARM Templates. API skills. This position pays between 30LPA - 35 LPA Depending on years of experience Show more Show less