Skip to main content

Nirav Madhani

Machine Learning Engineer

About Me

I'm a Software Engineer passionate about building intelligent applications and scalable cloud infrastructure. With a background in AI and full-stack development, I enjoy tackling complex problems and turning ideas into robust, production-ready solutions.

My experience spans from developing RAG-powered chatbots and optimizing Java microservices to designing scalable systems on Azure. I'm always eager to learn new technologies and contribute to innovative projects.

Experience

Application Developer II

Sep '23 - Present
ARGO DATA, Richardson, TX
  • Optimized various API features, saving 182,520 vCPU-minutes annually for over 500,000 users.
  • Contributed to setting up Azure Monitor and Alerts, reducing problem detection time by 15 minutes and solving time by 7 minutes per incident.
  • Re-architected the application for VNet implementation, mitigating security risks and accelerating database calls by more than 300%.
  • Led the development of an LLM-powered AI chatbot for surveys using the LangChain Agents framework, achieving 3x faster development.
  • Performed LoRA based finetuning, yielding a 10% average improvement across all benchmarks.
AzureLangChainPythonLLMOpsMLOpsFinetuningAgentsMonitoringOptimizationJavaAgile

Application Developer I

Sep '22 - Aug '23
ARGO DATA, Richardson, TX
  • Increased UI performance by 20% and averted security risks worth over $200,000 by upgrading React libraries and migrating to MUI v5.
  • Helped increase efficiency by 6x for generating high-quality LLM finetuning data by creating a React-based data visualization dashboard.
  • Migrated applications from monolithic architecture to Azure microservices, reducing infrastructure costs by $20,000 annually.
AzurePythonLLMOpsEDAFinetuningAutomationReactPipelinesDockerContainers

Full-Time Research Intern

Jan '22 - May '22
Indian Space Research Organization
  • Optimized a hyperspectral super-resolution model, improving processing speed by 30% for large-scale satellite remote sensing.
  • Improved image resolution from 20m to 5m, impacting 442 million acres of forest and agricultural land.
  • Conducted spectral resampling on over 1TB of data, increasing model accuracy by 8%.
Deep LearningComputer VisionHigh Performance ComputingPyTorchMXNet

Recent Projects

No projects to display.

Education

M.S. in Computer Science

Sep '23 - Dec '25

University of Texas, Austin

GPA: 3.75

Coursework: Reinforcement Learning, Deep Learning, Robotics Control, Online Learning & Optimization

B.Tech. in Computer Science & Engineering

Jul '18 - Jun '22

Nirma University, India

Coursework: Cloud Computing, Data Mining, Machine Learning, Scientific Computing, Big Data Analytics

Skills

Programming Languages

PythonJavaC++C#VB.NetJavaScript

Databases

MySQLSQL ServerPostgres SQLMongoDBCassandraPinecone

Frameworks

DjangoFlaskSpring BootBootstrapReactNode.js

Cloud Platforms

AWSAzureGCPDockerKubernetesOpenShiftDigital OceanServerless Functions

Machine Learning

LLMsNLPVision-Language ModelsRAGTime-SeriesPyTorchTensorFlowLangChainONNXscikit-learnllama-indexCausalityModel EvaluationMLOpsLLMOps

Misc

GitHubJenkinsGraphQLRESTAgileJiraROSJSON-RPCAgentsChain of ThoughtAPI CompositionBusiness & IT Automation