Manoj Hegde
Currently working as an AI/Software Engineer at Mercedes-Benz AG, building agentic RAG microservices and automated ML/software pipelines. Master's Student in Computer Science specializing in Data Science & AI Security.
Experience
Research
Education
Paderborn University
Master's in Computer Science
Specialization in Data Science & Computer Security. Paderborn, Germany.
Global Academy of Technology
2020 - 2024B.E. in Computer Science
Info & Comm Technologies (EQF Level 6)
Languages
Featured Projects
Cost-Optimized Serverless RAG on AWS
A strategic GenAI solution designed to minimize inference costs. Implements a serverless 'Smart Router' using AWS Lambda to dynamically direct queries between low-cost models (Amazon Titan) and high-intelligence retrieval workflows (Claude 3 + S3), ensuring finding the right balance between performance and budget.
SentinLLM: Automated Guardrails & Eval Pipeline
A production-grade LLM Ops system ensuring AI safety. Features a 'Smart Proxy' that enforces active guardrails, retrieves private context via RAG (ChromaDB), and runs automated 'LLM-as-a-Judge' evaluations.
FleetGuard: Real-Time Anomaly Detection
An end-to-end streaming MLOps pipeline that ingests vehicle telemetry via Kafka, utilizes Feast for low-latency feature retrieval, and detects driving anomalies instantly using unsupervised learning.
End-to-End MLOps: Predictive Maintenance API
A fully automated, serverless MLOps pipeline. It uses Terraform for Infrastructure as Code, DVC for data versioning, and GitHub Actions to deploy a FastAPI model directly to AWS Fargate on every push.
Ready to build something amazing?
I'm currently looking for new opportunities in Cloud Engineering and MLOps. Whether you have a question or just want to say hi, my inbox is always open.
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