
Hey — I'm Adi.
Applied AI engineer.

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.
Data Engineering Professional Certificate
Deep Learning Specialization
Machine Learning Specialization
PyTorch for Deep Learning Professional Certificate
The trip
Four legs — analyst work, hardened backends, quant product, and mission-critical applied ML.
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).
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.
SheeldS (Arilou Automotive Cybersecurity)
Ramat Gan · part-time
Backend R&D in automotive cybersecurity: engineered a recursive Python hex parser decoding low-level CAN telemetry into structured data models. Built Python & C# utilities for log normalization, signal extraction, and troubleshooting workflow automation. Operated within ASPICE & ISO 21434-compliant cross-functional processes.
Nebius Israel
Tel Aviv · part-time
High-volume web data acquisition at Nebius (ex-Yandex): extracted and structured large-scale external datasets into reliable analysis-ready assets. Delivered actionable insights through advanced analytics. Automated recurring collection pipelines for operational scale.
Selected work
Quant platform, defense-scale ML/CFD stacks, and production backends — links where public.
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.Built for edge deployment and mission-critical counter-UAS workflows, with sub-meter micro-target tracking under real-world latency constraints.

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.Turns live wind, wave, and ocean telemetry into actionable routing intelligence for operators navigating shifting marine conditions.

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.Bridges raw geospatial inputs and CFD-ready meshes so teams can run water and wind flow analysis without manual prep overhead.

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