Machine Learning Ops Professional

BAY Area Technology Solutions; Pune District; On-site; INR 700,000 - 1,000,000; Full time

Job summary

BAY Area Technology Solutions is seeking a Machine Learning Ops Engineer who will be responsible for managing and optimizing the deployment of machine learning models in production environments.

The ideal candidate will work closely with data scientists and DevOps teams, designing secure and scalable infrastructure in Azure and maintaining CI/CD pipelines to ensure seamless integration of models into existing systems.

Qualifications

• Strong understanding of MLOps practices and Azure cloud.
• Hands-on experience with Docker and Kubernetes.
• Experience in implementing Data/Model drift.

Responsibilities

• Design and implement scalable Azure infrastructure.
• Build and maintain CI/CD pipelines for data science.
• Automate infrastructure provisioning and demand forecasting.
• Monitor system health and security controls.

Skills

Machine Learning concepts

Azure Cloud practices

Python scripting

Docker

Kubernetes

Git

Continuous Integration

Monitoring tools

Troubleshooting

Job description

• Machine Learning Ops Engineer is the one who is 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 system 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 new cutting-edge technology with right value proposition