DevOPs/MLOPs Engineer

1 month ago

pune, India Quess Corp Limited Full time
Job Description Summary
MISSION : The MLOPs responsible to manage AIML solution deployments across all technical environments, from development to production, using MLOPS culture and IT practices. This includes ensuring the availability and usability of the provided solutions, providing technical support for building, installation, deployment, and testing of the solutions, and offering Level 3 technical support to operations teams.
Role & Responsibilities –
- Responsible for design and implementation of Application MLOPs frameworks.
- Responsible for Model and Data Drift frameworks.
- Build and maintain CI/CD/CT pipeline across azure cloud platform for Data science projects.
- Experience in MLFlow.
- Envision, implement and rollout best MLOPs/DevOps tools and automation.
Requirements:
- 7+ years of experience in the field of DevOPs/MLOPs
- Hands on Experience in Azure DevOps practices and building release pipelines.
- Build and maintain CI/CD/CT pipeline across azure cloud platform for Data science projects.
- Proficient in Azure Cloud practices and managing Azure Kubernetes Service deployments
- Good to have Hands on experience in Python or any other scripting languages (Groovy, Shell)
- Experience in Databricks, MLFlow deployment pipeline will be an added advantage
- Experience with monitoring tools like Prometheus, Grafana, App Insights etc
- Hands-on experience in Docker, Kubernetes.
- Excellent experience with source code management tools (git)
- Good to have experience in implementing Data/Model drift.
- Strive for Continuous Improvement and build continuous integration, continuous development and Continuous deployment pipeline
- Excellent Troubleshooting skills
- Always ready to learn more and adopt new cutting edge technology with right value proposition.
- Nice to have knowledge on Dataiku devops.
Job Description
KEY EXPECTED ACHIEVEMENTS
Business understanding & Solution implementation
• The business need is understood and formalized in a descriptive datasheet or specifications
• The methods are identified through external researches and selected by their theoretical bases, advantages and drawbacks.
Roles & Responsibilities:
- Responsible for design and implementation of Application MLOPs frameworks.
- Responsible for Deploying the ML Model end to end
- Expert on Azure DevOps Pipelines
- Responsible for Model and Data Drift frameworks.
- Build and maintain CI/CD/CT pipeline across azure cloud platform for Data science projects.
- Experience in MLFlow.
- Envision, implement and rollout best MLOPs/DevOps tools and automation.
- Nice to have LLMOPS knowledge

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