Systems Architect (DevOps & MLOPs)

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

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)