Hey — I'm Adi.

Applied AI engineer.

Adi Vardi
Machine Learning · Quant · Systems · Deep Learning · FullStackMachine Learning · Quant · Systems · Deep Learning · FullStack

About

I

am

an

applied

AI

engineer

working

at

the

intersection

of

machine

learning

computational

modeling

and

production

systems.

I

build

end

to

end

AI

infrastructure

research

modeling

algorithmic

design

backend

architecture

automation

pipelines

and

deployment

in

demanding

multidisciplinary

R&D

environments.

I

care

about

scientific

rigor

operational

reliability

and

long

horizon

systems

thinking

especially

for

physics

driven

data

intensive

problems.

Autodidactic collaborative and growth driven excellence distinctions from military and Ministry of Education. Open to collaborations where ambitious engineering meets real world impact.

Skills

JavaScript
TypeScript
React
Python
C#
Git and GitHub
HTML
CSS
SQL
Machine learning
Deep learning
Amazon Web Services
Google Cloud Platform
Linux

Intra stack

TensorFlow
PyTorch
OpenCV
Scikit-learn
Supabase
Vercel
Railway
PostgreSQL
Apache Kafka
TradingView
Claude (Anthropic)
Cursor
CrewAI
Hugging Face

Ask me anything

Ask about Adi
Ask about Adi’s work, stack, or how to connect — answers stay grounded in what’s on this site.

The trip

From data foundations to defense-scale AI

Four legs — analyst work, hardened backends, quant product, and mission-critical applied ML.

  • Now

    Applied AI Engineer

    Israeli Military Intelligence · INI

    Tel Aviv · on-site

    Elite multidisciplinary R&D: AI-driven computational systems for physics-heavy domains, end-to-end data pipelines, ML/DL in performance-critical simulation-adjacent stacks. INI Commander’s Excellence Distinction (2026).

  • Parallel

    Founder · Trader

    Quantrade

    Remote

    Quant equity & macro work plus Quantrade: private portfolio optimization SaaS — ML recommenders, risk-parity allocation, Monte Carlo engines, systematic construction grounded in modern portfolio theory.

  • 2022

    Backend Python Developer

    SheeldS (Arilou Automotive Cybersecurity)

    Ramat Gan · part-time

    Fleet-scale automotive cyber telemetry: Python parsers from CAN to threat-ready models, automation for logs and IR in ISO 21434-grade production.

  • 2021

    Data Analyst

    Nebius Israel

    Tel Aviv · part-time

    Large-scale web acquisition, unstructured → analysis-ready assets, automated pipelines and reporting for scale and reliability.

Selected work

Quant platform, defense-scale ML/CFD stacks, and production backends — links where public.

Quantrade

Quantitative finance platform — portfolio optimization SaaS with ML-driven signals, risk-aware allocation, and simulation-backed workflows. Live product.

Quantrade preview
SkyGuard-ML

SkyGuardML is a real-time detection and tracking system optimized for tiny aerial objects, combining a custom YOLO11 architecture with advanced tracking and post-processing to achieve high-accuracy performance on challenging micro-targets. It integrates detection, tracking, analytics, and visualization into a unified pipeline for scalable, production-grade aerial surveillance.

SkyGuard-ML preview
WaveR

WaveR is a high-resolution ocean forecasting and routing engine that combines real-time wind, wave & advanced metrics data with interactive visualization to support marine decision-making. It enables users to analyze forecasts at any point or plan optimized multi-leg routes with dynamic conditions and ETA calculations.

WaveR preview
TerraFlow

TerraFlow is a data-to-simulation pipeline that converts real-world terrain and building data into CFD-ready environments for accurate water and wind flow analysis. It automates the full workflow—from geospatial ingestion to simulation outputs—enabling scalable, physics-based environmental modeling.

TerraFlow preview
Automotive cyber telemetry

ISO 21434-aligned CAN parsing, structured threat models, and backend automation for fleet-scale detection platforms (SheeldS / Arilou).

Automotive cyber telemetry preview

More detail in conversation.

Let’s build something sharp

Best first touch is LinkedIn — or email if you prefer a longer brief.

adivardi2005@gmail.com