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RenoX23/README.md
Renold Stephen R — AI Systems, Production MLOps, Data Platform

Portfolio LinkedIn Email GitHub



Production Vitals & SLA Benchmarks

01 // IDENTITY · PROFESSIONAL OVERVIEW

Professional Profile & Engineering Overview — Renold Stephen R
▸ View Accessible Bio & Systems Overview

AI/ML Engineer (M.Tech CS) specializing in Generative AI, production MLOps, and scalable decision intelligence. Backed by engineering internships at CDAC, IBM Cloud, and Mesanite (IIIC), with published computer vision research and a registered copyright with the Government of India.

Architects containerized AI microservices backed by automated CI/CD pipelines, in-memory feature stores, and statistical observability (KS-tests, PSI) to deliver reliable, SLA-bound production systems.

  • Core Competencies: Agentic AI Workflows · Hybrid RAG (BM25 + Cross-Encoders) · Sub-20ms ML Inference · Real-Time Drift Observability · Star Schema Data Modeling.
  • Engineering Standard: Moving beyond isolated notebook experiments into containerized, observable, and SLA-bound production systems.

02 // CORE DOMAINS (WHAT I BUILD)

[01] AGENTIC AI & RAG

Dense/sparse hybrid retrieval (ChromaDB + BM25 + RRF), BGE cross-encoders, citation guardrails, and automated evaluation using Ragas.

[02] LOW-LATENCY ML

Cost-weighted gradient boosting fused with zero-day anomaly detection, clearing sub-20ms P99 SLAs with zero temporal leakage.

[03] PRODUCTION MLOPS

Covariate shift detection via KS-tests and Population Stability Index (PSI), pre-allocated SHAP microservices, and CI/CD pipelines.

[04] DATA PLATFORMS

In-memory Redis feature stores (ZSET velocity counters), analytical data marts (DuckDB), and PostgreSQL Star Schemas with CTE window functions.

03 // FLAGSHIP PRODUCTION SYSTEMS

IndicCompliance: Financial Regulatory Hybrid RAG Real-Time Payment Fraud Detection Engine
B2B SaaS Churn Early-Warning & MLOps Platform Supply Chain & Unit Economics Analytics
▸ Open-Source Developer Tooling & Infrastructure

🧩 AI Agent Workflow Builder

Visual DAG orchestration for multi-step AI agent workflows. Composes, inspects, and debugs agentic execution traces without black-box abstractions.
TypeScript AI Agents Workflow Orchestration

🔨 DataForge

Controllable synthetic dataset generation engine designed around schema constraints and realistic distributions rather than toy random noise.
Python Data Engineering Synthetic Data

🧠 GenAI Data Quality Explainer

Automated root-cause diagnostic engine that translates data pipeline anomalies and expectation violations into structured, actionable remediation steps.
Python GenAI Data Observability

🔁 GitOps & MLOps CI/CD Control Plane

Production-grade deployment pipeline managing containerized ML workloads across Kubernetes with automated Canary rollouts and Git as the single source of truth.
Kubernetes GitOps ArgoCD MLOps

04 // PRODUCTION TECH STACK

[01] AI, LLMS & INFERENCE

AI & Inference Stack

LangGraph LangChain Groq LLaMA-3.3 ChromaDB Ragas LightGBM BGE Cross-Encoder

Dense/sparse hybrid retrieval (BM25 + BGE), Ragas faithfulness guardrails, Groq 4.0ms LLaMA inference, cost-weighted LightGBM.

[02] DATA & FEATURE STORES

Data & Feature Stores

DuckDB Redis ZSET Star Schema Window CTEs Pandas NumPy SciPy CSR Sparse

In-memory feature velocity (1.14ms ZSET), DuckDB analytical data marts, Star Schema data modeling, sparse matrix compression.

[03] MLOPS & OBSERVABILITY

MLOps & Observability

Evidently AI SHAP TreeExplainer MLflow FastAPI Drift Detection Prometheus

Covariate shift drift detection via KS-tests & PSI, pre-allocated SHAP TreeExplainer microservices, cluster health observability.

[04] CLOUD, INFRASTRUCTURE & BI

Cloud, Infra & BI

Kubernetes HPA AWS Terraform Power BI DAX Streamlit Jenkins

Autoscaling pod clusters (2 → 8 pods, p95 < 300ms), Terraform IaC pipelines, executive Power BI and Streamlit dashboards.

05 // RESEARCH, CREDENTIALS & PEDIGREE

💼 Engineering Experience

  • Mesanite Software Solutions (IIIC, Bengaluru)
    NLP Research Intern [May 2026 – Jun 2026]
    • Developed GapIQ: Hybrid NLP matching engine fusing 5D semantic scoring with Groq LLaMA-3.3 (4.0ms inference latency).
    • Benchmarked 5 NLP architectures: +317% F1 lift over TF-IDF (F1=0.547, $p &lt; 0.05$).

  • CDAC (Centre for Development of Advanced Computing, Bengaluru)
    IT & DevOps Intern [Dec 2025 – Jan 2026]
    • Provisioned AWS infrastructure via Terraform; configured Kubernetes Horizontal Pod Autoscaling (HPA scaling 2 → 8 pods).
    • Sustained p95 latency < 300ms under burst workloads with Jenkins CI/CD & Prometheus alerts.

  • IBM Cloud, Bengaluru
    Cloud Intern [Oct 2024 – Feb 2025]
    • Orchestrated containerized deployment pipelines on IBM Kubernetes Service (IKS).
    • Configured Prometheus & Grafana dashboards for real-time node health & cluster telemetry.

📜 Intellectual Property & Education

  • Published Research Paper
    Computer Vision & Assistive Navigation
    YOLOv5 + Raspberry Pi Edge Assistive Navigation for Visually Impaired.

  • Registered Intellectual Property
    Co-authored 1 Copyright Registered with the Copyright Office, Government of India.

  • Open Data & Community
    • Published 5+ Public Kaggle Datasets for ML, analytics, and research.
    • 4+ Open-Source Tools released on GitHub.
    • Microsoft Learn Student Ambassador (MLSA).

  • Certifications
    • Microsoft Certified: Azure Fundamentals (AZ-900)
    • Generative AI — Google Skill Builder
    • Exploratory Data Analysis — Accenture

  • Academic Background
    • M.Tech in Computer Science [2025 – 2027]
    Christ University, Bengaluru — CGPA: 3.67 / 4.0
    • B.Tech in Information Science & Engineering [2021 – 2025]
    Cambridge Institute of Technology, Bengaluru — CGPA: 8.36 / 10.0

06 // LIVE TELEMETRY · REPO ACTIVITY

GitHub Telemetry — RenoX23



Followers Stars Profile Views

07 // DISPATCH · DIRECT CHANNELS

> "The hard part of AI isn't the prototype — it's the system:
   the latency bounds, the citation guardrails, the data integrity,
   and the observability that keeps it working in production."

> let's build something useful together.

Direct Email  LinkedIn Profile  Portfolio Site



Engineered with precision · Hosted on GitHub · Automated continuous integration

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  1. regulatory-compliance-hybrid-rag regulatory-compliance-hybrid-rag Public

    Enterprise Hybrid RAG system over RBI and SEBI financial regulations combining ChromaDB dense search with BM25, cross-encoder reranking, and quantitative Ragas evaluation.

    Python 1

  2. quick-commerce-supply-chain-analytics quick-commerce-supply-chain-analytics Public

    End-to-end supply chain analytics warehouse modeled in PostgreSQL (Star Schema) and Power BI tracking dark-store stockouts and vendor OTIF SLA adherence.

    Python 1

  3. saas-cohort-retention-analytics saas-cohort-retention-analytics Public

    24-month SaaS subscription retention engine constructing triangular monthly cohort matrices and modeling LTV:CAC unit economics in SQL and Python.

    Python 1

  4. ecommerce-market-basket-affinity-analysis ecommerce-market-basket-affinity-analysis Public

    Prescriptive retail cross-sell engine utilizing FP-Growth/Apriori association rule mining and SQL data marts to optimize Average Order Value (AOV).

    Python 1

  5. realtime-payment-fraud-redis realtime-payment-fraud-redis Public

    Low-latency financial fraud detection engine utilizing LightGBM and Redis in-memory feature caching, evaluated strictly on PR-AUC and Precision@Top-100 for extreme class imbalance.

    Python 1

  6. saas-churn-early-warning-mlops saas-churn-early-warning-mlops Public

    Production B2B SaaS account health and churn early-warning microservice with LightGBM, containerized in Docker with FastAPI, GitHub Actions CI/CD, and Evidently AI Slack drift alerting.

    Python 1