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Systems Architect (DevOps & MLOPs)

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Data DevOps, Systems Architecture, MLOps, MLflow, Apache Airflow, Kubeflow, CI/CD, Infrastructure, Prometheus, Grafana
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Hyderabad, Bangalore

We are seeking a Systems Architect (DevOps & MLOPs) to join our team. In this role, you will be an integral part of our solution architecture team, focusing on designing and implementing data infrastructure and DevOps solutions for our projects. If you have a passion for data architecture and DevOps, and a strong foundation in systems architecture, MLOps, MLflow, Apache Airflow, Kubeflow, CI/CD, infrastructure, Prometheus, and Grafana, we encourage you to apply.

Responsibilities
  • Shorten development cycles for our software and AI/Client systems
  • Build and maintain tools and infrastructure for efficient software and AI/Client development
  • Help us build and automate our AI/Client workstream from data analysis, experimentation, operationalization, model training, model tuning to visualization
  • Build and maintain data pipelines for analytics, model evaluation and training (includes versioning, compliance, and validation)
  • Train and Re-train systems when necessary
  • Improve and maintain the automated CI/CD pipeline
  • Increase the deployment velocity, including the process for deploying models and data pipelines into production
  • Build and maintain infrastructure as code (IaC) in the cloud, that can scale when needed
  • Collaborate with engineering team to develop, deploy and maintain our products with ease
  • Ability to take on substantial responsibilities from the first day and the opportunity to directly shape our full CI/CD+ infrastructure
Requirements
  • 10 + years of strong experience in MLOPs
  • Solid experience in designing, building DevOps pipelines for ML models/apps and different environments required for Dev/Test/UAT/Prod
  • Experience in providing quick solutions/fixes to the production issues on ML models
  • Experience with Monitoring/Alerting systems for model failures, data failures, real time scoring failures etc.
  • Experience in selecting appropriate datasets and data representation methods
  • Able to Perform statistical analysis and fine-tuning using test results after running the machine learning tests and experiments
  • Proven programming skills with multiple programming languages: Python/Java or similar
  • Shell scripting and Unix OS skills are necessary
  • Solid experience with Software engineering good practices, especially DevOps practices
  • Excellent problem solving and debugging skills
  • Strong experience with Cloud infrastructure on any of GCP/AWS/Azure cloud platforms. Experience in GCP is preferrable
  • Familiar with tools such as Apache Airflow, DVC, MLFlow etc.
  • Certifications Preferred: Certification from any of the three major cloud platforms (AWS / Azure / GCP) in Cloud DevOps / Architecture / Engineering
Nice to have
  • Familiarity with Data Science and ML concepts
  • Computer Science graduate (BTech/BE or higher)