AI/ML Engineer · Python Backend Developer · Flutter Developer
From computer vision and RAG pipelines to FastAPI services and Flutter apps, I build the reliable layers that make AI useful to people and teams.
Selected work
Case studies that show the technical decisions behind model delivery, APIs, and product experience.
View all projectsA consent-first, multi-tenant voice platform with real-time synthesis, evaluation, and production-minded controls.
Designed beyond the model layer: enrollment checks, async workloads, observability, audit logs, and streaming delivery are part of the system.
Computer vision for parking operations, turning calibrated camera feeds into occupancy signals and practical analytics.
Built around the operational layer as much as detection: polygon calibration, live updates, API design, storage, and a dashboard.
An end-to-end churn analytics system that connects modeling, explanations, retention actions, and monitoring.
The project makes a better hiring signal than a notebook: it includes ingestion, feature engineering, API serving, an analytics dashboard, and automation.
A public Flutter client for Gemini with local history and a conversational interface—87 stars and 17 forks on GitHub.
This is the mobile product signal: an approachable AI interface, maintained as a real open-source Flutter repository rather than a one-off UI exercise.
GitHub activity
Recent repositories, curated for technical relevance and refreshed from GitHub.
This Flutter application provides a conversational interface with Gemini
platform for consented voice enrollment, synthesis, real-time streaming, voice conversion, quality evaluation, and agent-driven workflow orchestration.
Computer-vision parking operations platform built with Python, FastAPI, OpenCV, YOLOv8-compatible detection, slot polygon calibration, analytics APIs, WebSockets, SQL-ready storage, and a React dashboard.
A churn prediction system which covers data ingestion, feature engineering, model training, explainability, retention recommendations, FastAPI serving, Streamlit analytics, monitoring, and cron-ready automation.
Capabilities
I connect model development, FastAPI and Django services, and Flutter interfaces into dependable end-to-end products.
Experience
Hands-on AI and Flutter work, informed by computer science study and publicly visible engineering practice.
Worked on a Django-based telecom chatbot backend with retrieval, live package data integration, caching, and backend support workflows.
Freelance AI/ML engineering work building machine learning systems, model training pipelines, and AI-backed product features for international clients.
Building and delivering production-grade Flutter applications with focus on responsive UI, state management, and delivery-ready quality.
Coursework spanning programming foundations, core systems, databases, artificial intelligence, software engineering, web delivery, project work, internship-based learning, and selected electives in multimedia, commerce, project management, and cloud topics.
Secondary science education with focus on physics, chemistry, and mathematics fundamentals.
Let’s work together
Open to AI/ML, Python backend, and Flutter engineering roles. Tell me what you are building, where it is getting difficult, and what success needs to look like.
dc.aayush.dangi@gmail.comStart a conversation