Nithin R
AI Platform Engineer @ AstraZeneca
Chennai, India
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ML Platform Engineer | AstraZeneca
Building and scaling enterprise-grade machine learning platforms from the ground up is my passion. At AstraZeneca, I'm at the forefront of developing a robust, ML platform using a powerful suite of open-source technologies. This platform empowers our data scientists and machine learning engineers to accelerate the development and deployment of impactful AI solutions.
My work involves designing, implementing, and maintaining the core infrastructure of our ML platform. I leverage a range of cutting-edge tools, including:
LLM Serving: NVIDIA Dynamo, GPU Operator, KAI Scheduler
Orchestration & Workflow: Kubeflow, Ray, Volcano Scheduler
Experiment Tracking & Model Registry: Weights & Biases
Monitoring & Observability: Grafana, Prometheus, ELK stack
Containerization & Registry: Harbor
Storage: NetApp Ontap FSx
Security & Governance: Kyverno
CI/CD: GitHub Actions, ArgoCD, Argo Rollouts
Database: CloudNativePG
I am deeply involved in all stages of the platform lifecycle, from initial design and architecture to deployment, maintenance, and continuous improvement. This includes automating infrastructure provisioning, optimizing resource utilization, ensuring platform stability and security, and collaborating with various teams to understand their needs and provide effective solutions. I thrive in a collaborative environment and enjoy tackling complex challenges related to distributed systems, scalability, and performance. I'm passionate about building robust and reliable ML platforms that empower data-driven innovation in the pharmaceutical industry.
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Kubeflow Virtual Sessionize Event
Kubeflow Virtual Planning Symposium 2025
Kubeflow for enabling AI Powered Drug Discovery and development in AstraZeneca - Shrinidhi Venkataraman & Nithin R, AstraZeneca
AstraZeneca’s robust AI platform, Azimuth—their first enterprise cloud-native machine learning platform—relies heavily on Kubeflow to power scalable and efficient AI workflows. In this session, we’ll explore how Kubeflow supports diverse AI use cases, with each project operating in its own dedicated namespace and persistent volumes ensuring durable data storage. We’ll cover how to enable cross-namespace volume access, build custom Kubeflow notebook images with VS Code and other editors, and use self-hosted GitHub runners to trigger pipelines. You’ll also see how integrations with tools like Grafana, ArgoCD, and Argo Workflows enhance the platform’s functionality. To maintain security and compliance, custom image governance is enforced through Kyverno policies. Finally, we’ll introduce the GreenOps framework—a set of practices focused on building sustainable AI solutions. Join us for an in-depth look at how Kubeflow powers enterprise-scale AI at AstraZeneca.
https://www.youtube.com/watch?v=kodLbDsav9A
KubeCon + CloudNativeCon India 2024 Sessionize Event
KubeCon + CloudNativeCon India 2024
Showcased Azimuth - AstraZeneca’s cutting-edge Enterprise Cloud Native Machine Learning Platform. It is built on Kubernetes and integrates a diverse array of cloud-native tools, enabling seamless development, deployment, and management of machine learning workflows. My presentation will delve into the architecture, key components, real-world applications, and the integration with Cloudability for cost management, highlighting its role in empowering data science teams and accelerating innovation within AstraZeneca. The tech stack involves Kubeflow, Weights & Biases, Ray, Volcano Scheduler, Grafana, Prometheus, ELK, Harbor, NetApp Ontap FSx, Kyverno, GitHub Actions, ArgoCD, Argo Rollouts, CloudNativePG, etc
https://www.youtube.com/watch?v=k3SkyGNkcR4
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