sebastian@portfolio: ~/ai-agents

Shell · zsh

sebastian@portfolio ~/ai-agents % whoami
stdout sebastian_torres_ortiz

Sebastian Torres Ortiz

AI Agent Systems Engineer | Machine Learning Engineer | Automated Solutions Engineer
sebastian@portfolio ~/ai-agents % cat ./bio.txt
~/ai-agents/ bio.txt utf-8
Architecting autonomous AI agents that transform business operations. Built machine learning models deployed across 300+ retail brands, processing visual detections at scale to drive intelligent automation.

300+

brands served

5M+

predictions served

47%

efficiency gain

<12ms

inference latency

exit 0 · portfolio v2.0.0 · astro + react + typescript · retail ai

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contact --sebastian Available for AI agents, ML systems, and backend automation work.

projects / active deployment

Retail Intelligence In Production

Harmony · Colombia

Leading the machine learning work for Harmony, building product recognition systems that turn retail shelf images into detection, coverage, and brand execution analytics.

sebastian@harmony: ~/retail-vision

cv_pipeline.py
Retail shelf before product detection Retail shelf with detected products and confidence scores
sebastian@harmony ~/retail-vision % detect --products --country=co
products detected 142
brands matched 37
shelf share 84%

sebastian@risks-vision: ~/agentic-research

orchestrator.ts
agent map financial research automation
Router

Classifies user objective and dispatches the research flow.

User Profile

Reads capital, horizon, risk tolerance, and strategy constraints.

Market Intel

Combines price action, sentiment, macro, and structural signals.

Strategy Builder

Generates entries, invalidation, sizing, and trade scenarios.

Risk Engine

Stress-tests drawdown, exposure, leverage, and stop placement.

Analyst Report

Returns thesis, plan, risk notes, and market analysis.

prompt in

“Build a BTC/ETH strategy for my risk profile, include invalidation and market context.”

strategy state validated
risk mode controlled
analysis loop live

experience / skills

Sebastian builds AI agent systems with full-stack engineering depth.

This portfolio is about the systems I build: production AI agents, machine learning workflows, backend services, cloud infrastructure, databases, and frontend interfaces that make automation usable.

Machine Learning Head at HarmonyQuant ML anomaly detection · Reals Lab PropTech modelsProduction systems across backend, cloud, ML, and UI

sebastian@portfolio: ~/systems

Sebastian Torres Ortiz 0+ years of experience

Software developer focused on AI agents, ML products, and production-grade automation.

01 market + business data
02 agent planning
03 backend services
04 databases
05 cloud deployment
06 frontend interfaces
07 linux
sebastian@agent-lab ~/build % ship --agents --backend --cloud --frontend
Gemini LLM reasoning
Google Cloud GCP services
AWS cloud workloads
Linux distributions

Agentic Systems

Gemini workflowsMulti-agent orchestrationTool routingEvaluation loops

Backend Engineering

APIsPythonTypeScriptAsync workflows

Data & ML

Real estate AVMQuant anomaly MLFeature pipelinesModel serving

Cloud & Infra

AWSGoogle Cloud / GCPLinux distributionsProduction deployments

Frontend Product

AstroReactDashboardsInteractive UX

experience / real estate ml

Automated valuation models for Colombian apartment markets.

Built an XGBoost AVM that predicts price-per-m² from listing attributes, cadastral references, and locality signals — with explicit data-quality audits before training.

sebastian@realslab: ~/avm/apartments

train_avm.py
apartment avm 3,731 rows · price/per/m2
Ingest platform listings + cadastral
Audit 420 garage · 216 stratum fixes
Features locality · geo · cadastral/m²
Train XGBoost · price/m² target
Valuate apartment AVM inference

top feature importances

Stratum38.5%
Antiquity23.8%
Cadastral per m²21.3%
Garage13.4%
Area (m²)8.1%
Rooms5.3%
data audit 420 garage outliers capped · 216 stratum values normalized
train / test split 2,984 / 747
test rmse $374M COP
target price/m²

experience / listing quality ml

Automated audit of property listings on Colombia’s top platforms.

Built segment-specific XGBoost models that flag anomalous listings scraped from Finca Raíz and Metro Cuadrado — detecting pricing, attribute, and cadastral inconsistencies before they reach downstream systems.

sebastian@realslab: ~/listing-audit

audit_listing_xgb.py
listing audit 8,268 rows · 6 segments
Scrape Finca Raíz · Metro Cuadrado
Label 2,420 anomalies flagged
Segment city × property type
Train XGBoost per segment
Score anomaly probability

hold-out performance by segment

Bogotá Apartment
ROC 93.3% F1 74.4% Acc 85.1%
Bogotá House
ROC 92.9% F1 85.8% Acc 89.2%
Bogotá Studio
ROC 89.4% F1 84% Acc 83.8%
Medellín Apartment
ROC 97.8% F1 83.3% Acc 96.8%
Medellín House
ROC 95% F1 57.1% Acc 92.7%
Medellín Studio
ROC 92.2% F1 75.6% Acc 85.3%
label distribution 5,848 passed · 2,420 rejected · threshold 50%
features m² · geo · cadastral
avg f1 76.7%
run id 20260525

experience / quant ml · restricted

Quant machine learning for market anomaly detection.

Built production quant ML pipelines that flag structural anomalies across crypto, S&P 500, and gold — trained on 10+ years of multi-asset history. Live performance metrics remain confidential.

sebastian@quant-lab: ~/anomaly-detection

detect_anomalies.py
quant anomaly ml production · classified
Ingest 10+ yr OHLCV · macro feeds
Features regime · vol · momentum
Train quant ML detectors
Score anomaly probability
Deploy production · classified

monitored universe

CryptoS&P 500Gold
production metrics RESTRICTED
live detection precision
production alert rate
inference latency
portfolio symbols live

Live trading analytics, alert thresholds, and model scores are withheld — client-confidential production data.

history window 10+ years
symbol count 10+ assets
objective anomaly detect

experience / harmony geospatial

Retail census simulation for Bogotá’s store network.

At Harmony, I worked on data systems that collect more than 40k stores in Bogotá and transform them into simulation maps, density layers, microzones, and 1,000+ isochrones for a realistic census of the city.

sebastian@harmony: ~/bogota-retail-census

simulation_map.py
bogotá retail census 40k+ stores · 1k+ isochrones · microzones
retail density high activity corridor
1k+ isochrones microzone simulation
stores mapped 40k+
microzones 1k+
city census bogotá

experience / blockchain gaming

Unreal Destiny RPG with a decentralized game economy.

I worked as a smart contract developer on Unreal Destiny, an RPG where blockchain was used to keep the game economy transparent, auditable, and decentralized across multiple networks.

sebastian@bbstudios: ~/rpg-economy

contracts/GameEconomy.sol
Player Action quest / trade / reward
Smart Contract validates economy rules
Blockchain transparent settlement

contact / next collaboration

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