Venkata Sai Srujan Araveeti
Open to work4 years experienceMLOps Engineer
DevOps Engineer|MLOps Engineer
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Skills & Technologies
33 skillsGitHub Activity Evidence
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Work Experience
MLOps Engineer
National Payments Corporation of India (NPCI)
- Designed a Jenkins-based CI/CD framework integrated with Ansible, structuring modular pipelines where each stage invoked dedicated playbooks, reducing deployment and configuration errors by ~45% across environments.
- Architected and deployed a distributed Slurm cluster across 3 NVIDIA DGX nodes, configuring shared NFS storage, validating inter-node GPU communication via NCCL testing, and integrating SlurmDBD, Elasticsearch, and Filebeat for centralized job accounting and observability—enabling reliable scheduling for large-scale ML and HPC workloads.
- Authored and maintained Helm charts to standardize Kubernetes deployments across multiple applications, improving release consistency and significantly reducing onboarding time for new services.
- Deployed and operated LLM inference workloads and Triton Inference Server-based models on Kubernetes, optimizing GPU resource utilization and supporting scalable, low-latency model serving in production.
- Installed and managed NVIDIA GPU stacks across Kubernetes nodes and bare-metal servers using GPU Operators via Helm, configuring CUDA drivers and related libraries to support diverse ML workloads.
- Deployed and maintained Apache Druid for large-scale real-time analytics and Milvus vector database for similarity search, enabling efficient embedding-based retrieval for ML-driven applications.
- Built an end-to-end RAG application by ingesting Markdown documents into Milvus via embedding generation and integrating GPT-OSS-20B LLM, enabling semantic search and context-aware answers over organizational documents.
DevOps Engineer
Hitachi Digital Services
- Built and operated production-grade Kubernetes platforms deploying microservices and ML workloads using Deployments and StatefulSets, managing rolling updates and autoscaling—achieving 40% faster release cycles and improved application availability.
- Integrated Jenkins and GitLab CI/CD pipelines with AWS and Kubernetes, automating Docker image builds, ECR pushes, and EKS deployments, reducing manual intervention and deployment errors by ~50%.
- Designed and maintained Docker-based build workflows with optimized Dockerfiles and image management, ensuring consistent and reproducible runtime environments across all stages.
- Implemented secure Kubernetes configurations using ConfigMaps, Secrets, PersistentVolumes, and PVCs, enabling zero-downtime configuration changes and reliable state management for stateful services.
- Provisioned and managed AWS cloud infrastructure using EC2, S3, EKS, ECR, and IAM to support highly available, secure, and scalable production workloads.
- Automated cloud infrastructure and serverless components via CloudFormation templates, deploying AWS Lambda functions through GitLab CI/CD pipelines for event-driven processing use cases.
Projects
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Leaderboard Standings
Leaderboard Position Pending
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Assessment Highlights
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AI Collaboration Score
AI Collaboration Score Pending
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Role Compatibility Profile
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Achievements
TechnoWiz Award
TechnoWiz Award - Hitachi Digital Services
TechnoWiz Award
TechnoWiz Award - Hitachi Digital Services
Ninja & Wizard Awards
Ninja & Wizard Awards, Playground Challenge - NPCI
Ninja & Wizard Awards
Ninja & Wizard Awards, Playground Challenge - NPCI
About Details
Professional Bio
DevOps and MLOps Engineer with close to 4 years of experience designing Kubernetes-based infrastructure for large-scale ML and microservices systems. Skilled in GPU orchestration, distributed workloads, and automated CI/CD pipelines across AWS environments.
B.Tech in Computer Science and Engineering
Velagapudi Ramakrishna Siddhartha Engineering College (2018 - 2022)