Alexandre Ray da Silva
Verified Expert in Engineering
Artificial Intelligence Engineer and Developer
São Paulo - State of São Paulo, Brazil
Toptal member since June 1, 2026
Alexandre is a hands-on staff AI engineer with 11+ years of experience building production-grade AI and GenAI systems. He specializes in end-to-end AI development, including LLM applications (RAG, agents), ML pipelines, recommendation systems, and MLOps. Alexandre owns the full lifecycle from architecture to production, delivering scalable systems using Python, PyTorch, FastAPI, and cloud platforms. He focuses on solving complex, high-impact real-world problems.
Portfolio
Experience
- Python - 10 years
- Artificial Intelligence (AI) - 8 years
- Scikit-learn - 8 years
- Machine Learning Operations (MLOps) - 8 years
- SQL - 8 years
- Machine Learning - 8 years
- AI Agents - 3 years
- RAG Systems - 3 years
Preferred Environment
MacBook, Slack, Google Meet, React
The most amazing...
...thing i've built is OncoAI, a platform designed to help oncologists improve patient outcomes through AI-driven insights.
Work Experience
Co-founder & CTO
OncoAI
- Designed recurrence prediction models using structured clinical datasets for patient outcome forecasting.
- Developed AI-assisted treatment recommendation systems integrating retrieval pipelines and LLM-based reasoning.
- Architected back-end APIs and data services supporting clinical intelligence workflows.
- Built cloud-native deployment infrastructure for scalable healthcare AI applications.
- Led full-stack product development from system architecture through implementation and deployment.
- Collaborated with healthcare stakeholders to translate clinical requirements into production-ready technical solutions.
Staff AI/ML Engineer
IpsilonAI
- Designed and implemented production-grade retrieval-augmented generation (RAG) systems for enterprise log intelligence, reducing incident investigation time through automated contextual analysis.
- Built recommendation engines for store-level product optimization using collaborative filtering and ranking models, improving inventory decision support.
- Developed speech intelligence pipelines for automated English proficiency scoring using audio embeddings and deep learning inference systems.
- Architected distributed ML workflows using Apache Airflow and Azure Databricks for scalable model training and deployment.
- Optimized enterprise search infrastructure using vector retrieval systems and semantic indexing with OpenSearch.
- Delivered full production lifecycle ownership, including architecture, implementation, deployment, observability, and optimization.
Senior ML Engineer
Creditas
- Built credit risk scoring models that automated approximately 90% of operational credit desk workflows.
- Developed predictive systems for lead scoring, customer churn forecasting, and pricing optimization.
- Designed feature engineering pipelines for large-scale financial datasets.
- Implemented model monitoring and validation workflows to ensure production reliability.
- Collaborated with cross-functional business teams to operationalize predictive decision systems.
- Improved portfolio quality through statistically robust risk modeling.
Software Engineer
Service IT
- Engineered back-end services supporting large-scale digital media and enterprise web platforms.
- Led migration of high-traffic legacy websites to modern scalable architectures, including WordPress VIP environments.
- Developed RESTful APIs and database integrations to support content management workflows.
- Improved platform scalability and reliability through back-end performance optimization and infrastructure refactoring.
- Collaborated with front-end teams to integrate back-end services into responsive client-facing applications.
- Implemented database query optimizations that improved response time and system efficiency.
Software Engineer
BTG Pactual
- Developed internal back-end modules supporting fixed-income front-office and back-office operational workflows.
- Built SQL-based automation scripts for financial data processing and reconciliation tasks.
- Assisted in developing internal tools that improved operational efficiency for financial reporting pipelines.
- Implemented database procedures and back-end logic for transactional processing systems.
- Supported performance tuning of Microsoft SQL Server queries and data workflows.
- Collaborated with senior engineers to maintain the reliability and accuracy of financial operations infrastructure.
Experience
Legal Engine
https://github.com/alexandrerays/legal-engineMedical RAG
https://github.com/alexandrerays/medical-ragStock Agent
https://github.com/alexandrerays/stock-agentSpeech Flow AI
https://github.com/alexandrerays/speech-flow-aiEducation
Master's Degree in Computer Engineering
University of São Paulo - São Paulo, Brazil
Bachelor's Degree in Computational Physics
University of São Paulo - São Carlos, Brazil
Skills
Libraries/APIs
Scikit-learn, Pydantic, Asyncio, React, OpenCV, PySpark, Pandas, NumPy, vLLM, Node.js
Tools
Git, ChatGPT, You Only Look Once (YOLO), Pytest, Claude, Slack, Google Meet, Azure Kubernetes Service (AKS), GraphRAG, Claude Code, Codex, Apache Airflow, Terraform, Whisper, Microsoft Copilot, GIS
Languages
SQL, Python, OWL, JavaScript, Ruby, TypeScript, RDF, C#, PHP, Java, Rust, Snowflake
Frameworks
Agentic Frameworks, Angular, Django, Flask, LangGraph, Streamlit, LlamaIndex, Next.js
Platforms
Docker, Databricks, Amazon Web Services (AWS), LangSmith, Google Cloud Platform (GCP), Azure, Vercel, Replit, Kubernetes, Oracle, Microsoft Copilot Studio, Azure AI Studio, Kubeflow
Storage
PostgreSQL, Data Pipelines, MongoDB, Graph Databases, Neo4j, Datadog, MySQL, Redshift
Industry Expertise
Healthcare, Marketing
Paradigms
Model Context Protocol (MCP)
Other
Physics, Computer Science, Computer Vision, Object Detection, OOP Designs, Machine Learning, Machine Learning Operations (MLOps), MLflow, FastAPI, Artificial Intelligence (AI), LLM Integration, MacBook, Retrieval-augmented Generation (RAG), Agentic AI, LangChain, RAG Pipelines, Large Language Models (LLMs), AI Architecture, Product Development, API Integration, Prompt Engineering, Architecture, SDKs, Cursor AI, Pricing, Pricing Models, Natural Language Processing (NLP), eCommerce, Deep Learning, AI Design, Data Science, AI Programming, Ontologies, Knowledge Graphs, LLM Reasoning, Large Language Model Operations (LLMOps), Machine Learning (ML) APIs, AI Agent Orchestration, Semantic Code, Time Series Forecasting, 3D Pose Estimation, Motion Capture, Pose Estimation, Health, eye-tracking, Optical Character Recognition (OCR), Linear Regression, Bayesian Statistics, Statistics, Agentic RAG Systems, Anthropic, Convolutional Neural Networks (CNNs), Graph Neural Networks (GNNs), Pattern Recognition, Classification, Fine-tuning, Meta Llama, Observability, Algorithms, Trading, Cloud, RAG Systems, AI Agents, OpenAI, Healthtech, FAISS, Supabase, AWS Bedrock AgentCore, RAG Architecture, Vector Databases, Generative Artificial Intelligence (GenAI), Solution Architecture, Agentic Coding, Industrials, Data Labeling, Semantic Search, Eye Tracking, HIPAA, Model Evaluation, Vector Search, SQL Server, Data Architecture, Monitoring, Telemetry, Photoroom, Amazon Bedrock, Energy, Energy Efficiency, Energy Management, Energy Modeling, Biomechanics, life-sciences, Vehicle Tracking Systems, Vehicle Routing, GeoPandas, Data Security, Quantization
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