Venkat Balachandra

Project Manager

Bengaluru, Karnataka, India0 mo experience

AI EnabledAI ML Practitioner

Key Highlights

Reduced MTTR by 19.8% at Oracle.
Engineered lightweight image generation models.
Developed biomedical knowledge graphs for research.

Stackforce AI infers this person is a SaaS and AI/ML specialist with strong capabilities in platform engineering and data science.

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Skills

Core Skills

Platform EngineeringAiopsInfrastructure AutomationMachine LearningNatural Language Processing

Other Skills

Software InfrastructureSoftware DesignJVM DiagnosticsIncident ResolutionOAuth2HelmConfiguration ManagementComputer VisionKnowledge DistillationRectified FlowPython (Programming Language)Natural Language Processing (NLP)BERN2nltkEngineering

About

Currently contributing as a Project Intern at Oracle, focusing on designing and implementing robust platform engineering solutions. This includes building a JVM Diagnostics Platform to streamline diagnostics across Oracle Cloud environments and integrating AIOps workspaces to enhance operational efficiency for SRE and AMS teams. Pursuing a Bachelor of Engineering (Hons) in Computer Science Engineering and Data Science at RV College of Engineering, with a strong interest in autonomous vehicles, computer vision, and generative AI. Previous internships at TrueFoundry, AVEVA, Samsung R&D Institute, and HPCC Systems reinforced hands-on expertise in AI adoption, infrastructure optimization, and real-time system engineering.

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Oracle

Project Intern

Jan 2026 – Present · 5 mos · Bengaluru, Karnataka, India · On-site

Reduced MTTR by 19.8% by building a JVM Diagnostics Platform enabling on-demand diagnostics across 16 Oracle Cloud environments to speed up incident resolution; developed AI agent skills to integrate the entire workflow into our AIOps workspace.
Eliminated manual config drift risk across 47 Oracle Cloud Targets by architecting an OAuth2-authenticated Helm rollout tool that automated multi-region configuration management for all Observability Server Instances.
Unified fragmented AIOps tooling by refactoring bootstrap, credential management, k8s wrappers, MCP, and diagnostics features to integrate our division’s workspace into Oracle’s cross-division AIOps platform, delivering a seamless workstation experience.
Assessed production-readiness of two Oracle Cloud Services against 37 security and reliability controls, uncovering 33 failures spanning pod security, network policy, observability, and resource configuration.
Partnered directly with end-users to pilot our AIOps tool, gathering feedback that drove 21 targeted bug-fixes and enhancements

Software InfrastructureSoftware DesignPlatform EngineeringAIOps

Truefoundry

Software Engineer Intern

Aug 2025 – Dec 2025 · 4 mos · Bengaluru, Karnataka, India · Hybrid

Expanded AI Gateway capabilities by engineering support for multi-provider image manipulation, enabling diverse media processing workflows.
Enforced enterprise-grade security by implementing end-to-end identity management and team mapping, ensuring compliance with strict provisioning and access control standards.
Optimized system performance and resilience by deploying prompt caching, proxy support, and granular guardrail error handling within the AI Gateway.
Stabilized model cost tracking across the Kubernetes Controller and Server through targeted reliability engineering, ensuring accurate resource usage monitoring.
Broadened integration ecosystems by developing the LmChatTruefoundry node for n8n, exposing the AI Gateway as a native LangChain component for low-code automation.

Aveva

Software Development Intern

Jun 2025 – Jul 2025 · 1 mo · Bengaluru, Karnataka, India · On-site

Enabled proactive adjustments to meet customer commitments by engineering a real-time widget for early visibility into manufacturing shortfalls, leveraging Angular, RxJS, and Highcharts, and ensuring application reliability with comprehensive unit and Cypress end-to-end testing.

Samsung r&d institute india - bangalore

Virtual Intern

Jun 2024 – Apr 2025 · 10 mos · Hybrid

Worked extensively on creating efficient image generation diffusion models and explored various techniques such as knowledge distillation and rectified flow. Slashed inference from over 1000 steps to just 4 by engineering a lightweight image generation diffusion model (12.3MB) via
knowledge distillation and rectified flow, and achieving competitive image quality on a severely limited compute budget.

Machine LearningComputer Vision

Hpcc systems

Project Intern

Nov 2023 – Dec 2023 · 1 mo · Bengaluru, Karnataka, India · Hybrid

My HPCC internship focused on harnessing the power of NLP to unlock biomedical knowledge. I built a knowledge graph, like a map of linked genes, diseases, and drugs, extracted directly from scientific papers. Using tools like BERN2 and nltk, I automated the conversion process, making knowledge graph construction for biomedical use more accessible and cost-effective. This structured map connects scattered information, empowering researchers and clinicians with deeper analysis and the potential for personalized treatments.

Python (Programming Language)Natural Language Processing (NLP)Natural Language Processing