Tech Stack

Tools for ML, automation, cloud and security engineering.

My stack supports research-heavy work while still shipping practical systems, dashboards, validation flows and automation pipelines.

Python

PyTorch

GCP

Docker

Core Stack

Technologies grouped by engineering function.

Python

C++

Java

SQL

Python for automation and ML, C++ for systems-level work, Java for enterprise services, SQL for validation, and MATLAB for numerical workflows.

PythonC++JavaSQL

PyTorch

TensorFlow

OpenCV

pandas

PyTorch, TensorFlow, NumPy, pandas, scikit-learn and OpenCV for model development, data analysis, NLP and computer vision.

PyTorchTensorFlowOpenCV

GCPSpannerIAM

GCP and Cloud Spanner for backup, restore, schema comparison, IAM reporting and environment validation workflows.

GCPCloud SpannerIAM

Actions

SonarQube

Docker

Linux

Harness, GitHub Actions, SonarQube, Docker and Linux for CI/CD execution, quality gates and compliance reporting.

HarnessSonarQubeDocker

Flask

SQLAlchemy

MongoDB

Flask, SQLAlchemy, MySQL, MongoDB and API-driven tooling for internal applications, dashboards and workflow services.

FlaskSQLAlchemyMySQL

Cloud

GitHubIAM

IAM analysis, policy validation, defensive graph modeling, CI security gates and controlled lab evaluation for risk-aware engineering.

IAMPolicyRisk Analysis