Software systems
Production services, microservice architectures, data systems, observability, CI/CD, and cross-platform applications.
Software engineer · Independent researcher
Cristian
Camargo Filho
Building rigorous software systems at intersection of intelligent architectures, efficient computation, and human-centered tools.
Brazil · UTC−03
PythonRustDistributed systemsMachine learningPenetration testingCI/CDSvelteKitPostgreSQL
01 / Profile
Engineering depth, research mindset
From production backends to experimental systems.
My work spans production-grade services, microservice architectures, developer tooling, data systems, and cross-platform applications. Python is my strongest foundation; Rust expands that work into concurrency, systems integration, and computational efficiency.
I investigate information retrieval, agentic systems, local-first architectures, secure synchronization, and applied machine learning — especially where architecture and intelligent systems must remain practical, observable, and dependable.
Intelligent systems
LLM evaluation, agentic workflows, retrieval, automated audits for PII, bias and hallucinations, and AI-provider integrations.
Efficient computation
Runtime profiling, parallel execution, Python/Rust FFI, GIL-aware designs, and performance-sensitive system boundaries.
Security & delivery
Penetration testing and secure CI/CD with Jenkins, GitHub Actions, and Gitea Actions for private source-code management and delivery orchestration.
Selected systems & experiments
Work shaped by real technical questions.
Distributed systems2020 —
Myscelium
Python-first networking runtime backed by Rust, built for command routing, callbacks, synchronized state, and coordination across processes and machines.
Python / Rust interop2023
RustPyNet
GIL-aware execution experiments using PyO3, task queues, multithreading, controlled Python scopes, and bidirectional data transfer.
Semantic retrieval2023
PDF2Vector
Document vectorization with all-mpnet-base-v2, PCA dimensionality reduction, Euclidean similarity search, and K-Means clustering.
Developer tooling2024 —
Testrium
Python testing toolkit for verifying events, commands, requests, and messages across multi-process and service-to-service flows.
Local-first RAG2025
RagQL
Modular retrieval-augmented generation system for natural-language questions over logs and databases.
Applied machine learning2023
MultiLabelCNN
Convolutional neural-network experiments for image classification, dataset augmentation, and model analysis.
02 / Company
Zarpyon Corporation · Product company
Useful intelligence should strengthen human memory, not replace it.
Build dependable software that helps people organize, preserve, and retrieve digital knowledge with less friction.
Create intelligent, privacy-conscious tools where personal knowledge remains useful, portable, and under user control.
Flagship product SuperMemory
Digital study assistant for organizing, storing, and retrieving important information.
2022
Massachusetts Institute of Technology · IDSS
Data Science and Machine Learning: Making Data-Driven Decisions
Regression, recommendation systems, anomaly detection, hypothesis testing, network modeling, and data-driven decision making.
Focused study
- 01Data Science and Machine Learning
- 02Responsive Web Design with HTML/CSS
- 03Rust Systems Programming
- 04Deep Learning with PyTorch
- 05Deep Q-Learning
Architecture · AI · Applied research