- Machine Learning Ops Engineer is the one whos responsible for managing and optimizing the deployment and operation of machine learning models in production environments
- He/she works closely with data scientists, software engineers, and DevOps teams to ensure that machine learning models are integrated seamlessly into existing systems and can scale effectively

Role & Responsibilities

- Responsible for design and implementation of secure and scalable infrastructure in Azure cloud
- Build and maintain CI/CD/CT pipeline across azure cloud platform for Data science projects
- Own and automate the infrastructure provisioning, demand forecasting and capacity planning
- Build tools and automation to improve systems availability, reliability, performance, monitoring and scalability
- Setting up the alerts and monitoring for the platform
- Monitoring system, application health, security controls and costEnvision, implement and rollout best MLOPs/DevOps tools and automation

Requirements:





- Strong understanding of concepts related to Machine Learning, Architecture, and MLOps practices
- Proficient in Azure Cloud practices and managing Azure Kubernetes Service infrastructure
- Hands on experience in Python or any other scripting languages (Groovy, Shell)Experience with monitoring tools
- Hands-on experience in Docker, Kubernetes
- Excellent experience with source code management tools (git)Experience with modern cloud development practices such as Microservices Architecture, REST Interfaces etc
- Experience in implementing Data/Model drift
- Strive for Continuous Improvement and build continuous integration, continuous development, and constant deployment pipeline
- Excellent Troubleshooting skills
- Always ready to learn more and adopt recent cutting-edge technology with right value proposition

📌 Machine Learning Ops Professional (Pune)
🏢 Bay Area Technology Solutions
📍 Pune