OPEN TO WORK · BENGALURU / REMOTE

HarshaS MantrodiAI/ML & Cloud Engineer

$ engineer --building

AI/ML & Cloud Engineer specializing in Generative AI, Kubernetes, MLOps, and production-ready intelligent systems. From model training to production pipelines, cloud infra to MLOps — I ship end-to-end.

GitHubLinkedIn
3+
Internships
6+
Certifications
2
Domains: ML + DevOps
Drive to Build
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01 — About

Who I Am

Engineering-focused. Production-grade. Always shipping.

AI/ML EngineerMLOpsCloud & DevOpsGenerative AIComputer VisionNLP Systems

I'm Harsha S Mantrodi, an AI/ML & Cloud Engineer based in Bengaluru — operating at the intersection of machine learning systems and production cloud infrastructure.

Currently working as a DevOps Engineer Trainee at MATRIQZ AI, I wire together CI/CD pipelines, containerized ML deployments, and AWS cloud infra to make intelligent systems actually work in production.

My stack spans time-series forecasting, generative AI (SDXL/LoRA), NLP pipelines, computer vision, and cloud-native DevOps. I don't just train models — I architect production systems around them.

I think like a founder: every model has a customer, every pipeline has an SLA, every deploy needs to be bulletproof. That's the engineering mindset I bring to every role.

Available for Opportunities

ML / MLOps / DevOps — Full-time or Freelance

02 — Skills

Tech Stack

Full competency matrix across AI/ML, Generative AI, Cloud, and DevOps.

🤖

AI & Machine Learning

8 technologies

PythonPyTorchTensorFlowScikit-learnARIMA / LSTMNLP PipelinesComputer VisionPandas / NumPy

Generative AI

8 technologies

SDXL Fine-tuningLoRA TrainingHugging FaceRAG SystemsVoice AgentsGemini APIBLIP-2Diffusers
☁️

Cloud & DevOps

8 technologies

DockerKubernetesAWS (EC2/S3/IAM)JenkinsGitHub ActionsKubeSharkIngressLinux
⚙️

Backend & Tools

8 technologies

FastAPISQLGit / GitHubDatabricksGCPGoogle ColabVS CodeJupyter
03 — Projects

Things I've Shipped

Production-grade systems, not just experiments.

// AI / Generative
Production
Featured

BrandEngine AI

Production-Ready Minimalist Logo Generation for Startups

Custom AI engine trained on 800+ professional icons solving the brand consistency problem in generative AI. Delivers clean, flat-vector logos tailored to industry visual language — Agri-Tech, Fintech, Mechanical Engineering — optimized for clarity from favicons to large-scale print.

SDXLLoRAPyTorchDiffusersBLIP-2FP16Hugging Face
Key Highlights
Trained on curated 800+ icon library
FP16 precision + memory offloading for low-VRAM training
Automated BLIP-2 captioning pipeline
Industry-specific visual language adaptation
View on GitHub
☁️
// MLOps / Cloud
Production

Cloud-Native Sentiment Analysis System

Microservices ML Platform on Kubernetes

End-to-end containerized ML platform with FastAPI microservices, Kubernetes orchestration, and automated Jenkins CI/CD. Processes real-time sentiment at scale with horizontal pod autoscaling and zero-downtime deployments.

PythonFastAPIDockerKubernetesJenkinsGitHub ActionsLinux
GitHub
👁️
// Computer Vision
Shipped

AI Hand Gesture Recognition

Real-Time Computer Vision for Presentation Control

Real-time gesture recognition pipeline using MediaPipe hand landmark detection and LSTM deep learning. Low-latency inference optimized for standard webcam hardware with face detection integration.

PythonOpenCVMediaPipeTensorFlowLSTM
GitHub
📊
// ML / Analytics
Shipped

Car Sales Analysis & Price Prediction

Time-Series Forecasting with ARIMA + ML

Predictive pricing engine using ARIMA time-series forecasting and regression models on historical auto sales data. Full pipeline: data cleaning → feature engineering → model evaluation → trend analysis.

PythonARIMAScikit-learnPandasMatplotlib
GitHub
📊
// DevOps
Production

CI/CD Pipeline Automation

End-to-End DevOps Automation

End-to-end CI/CD pipelines automating build, test, and deployment workflows. Significantly reduced manual deployment effort and improved release reliability across environments.

JenkinsGitHub ActionsDockerBashGit
GitHub
04 — Experience

Where I've Built Things

Real environments, real systems, real impact.

DevOps Engineer Trainee

Current

MATRIQZ AI, LLP

Jan 2026 – Present

Full-Time

Deploying and managing ML workloads on AWS cloud infrastructure. Building CI/CD pipelines for ML and application deployments. Working with Docker and Kubernetes for scalable orchestration.

  • Deploying ML workloads on AWS (EC2, S3, IAM, CloudWatch)
  • Building CI/CD pipelines using Jenkins and GitHub Actions
  • Docker + Kubernetes for scalable application orchestration
  • Monitoring and automating AI/ML infrastructure at scale
AWSDockerKubernetesJenkinsCI/CD

Machine Learning Intern

Future Interns

Sep – Nov 2025

Internship

Built ML models for forecasting, churn prediction, and NLP chatbots. Handled the full ML pipeline from data ingestion to production-ready evaluation.

  • ML models for sales forecasting and churn prediction (10–15% improvement)
  • ARIMA time-series forecasting and NLP chatbot systems
  • Full pipeline: preprocessing → engineering → training → evaluation
  • Experiment tracking with Git/GitHub
PythonARIMANLPScikit-learnGit

DevOps Intern

Elevate Labs

Aug – Sep 2025

Internship

Contributed to cloud infrastructure management, CI/CD automation, and containerized deployments.

  • Automated cloud infrastructure workflows (~30% reduction)
  • CI/CD pipelines using Jenkins & GitHub Actions
  • Docker containerization and Kubernetes deployments
  • System reliability monitoring and performance metrics
DockerKubernetesJenkinsLinuxBash

B.E. in AI & Machine Learning

Current

St. Joseph Engineering College

2023 – Present

Education

Core AI/ML, cloud computing, data structures, and software engineering fundamentals. Mangalore, Karnataka.

  • Core AI/ML, cloud computing, data structures
  • Software engineering fundamentals and system design
  • Prior: Diploma in Tool & Die Making (2019–2022)
AI/MLCloudData Structures
05 — Certifications

Credentials

Verified certifications from Stanford, Google Cloud, AWS, and more.

🎓

Supervised Machine Learning: Regression & Classification

Stanford University

Coursera
🔧

Machine Learning Operations (MLOps) Fundamentals

Google Cloud

Google Cloud Skills
☁️

AWS Cloud Quest: Cloud Practitioner

Amazon Web Services

AWS
🏗️

AWS Solutions Architecture Job Simulation

Amazon Web Services

Forage
📊

Data Analytics Job Simulation

Deloitte Australia

Forage
🌐

Fundamentals of Cloud Computing

Cloud Certification Program

Online
07 — Contact

Let's Build Something

Open to full-time roles, collaborations, and ambitious projects.

Actively seeking ML Engineering, MLOps, or DevOps roles. Building something ambitious? In Bengaluru, remote, or anywhere — let's talk.

Available Now

Responding within 24 hours