About
AI Engineer with experience spanning computer vision, deep learning, robotics, and full-stack development. I build end-to-end ML pipelines, from data acquisition and model training to cloud deployment, and enjoy bridging the gap between research and production systems.
Publications
4 Scopus-indexed (INTERCON x2, ANDESCON x2) + 1 IROS workshop
Experience
AI Engineer
Oct 2025 - Present- Contributed to system design, technical coordination, and development of multiple AI projects
- Escania: Full-stack document defect detection platform with YOLO pipeline, SageMaker training, and serverless inference
- Ragia: Highly scalable Agentic RAG platform with hybrid retrieval, semantic chunking, and autonomous tool-calling agents
- Analitia: Automated QA system for call centers using AWS Transcribe and parallel AI agents
AI Implementation Engineer
Dec 2024 - Sept 2025- Implemented AI-Agents for automated sales using LLMs (OpenAI, Claude, Gemini), LangSmith, and prompt engineering
- Developed scripts and a CLI toolkit to streamline internal processes with MCP integration in Cursor
- Improved LangGraph-based prompt generation API, optimizing interaction quality and AI-Agent adaptability
Jr. Full Stack Developer
Mar 2024 - Dec 2024- Maintained and added features to Maersk Peru's order management platform, including import/export flows and document handling
- Implemented backend microservices in Python/Django integrated with Azure services
- Led a team of 3 developers expanding the financial back office for BCP account transfers
Computer Vision Engineer
Nov 2024 - Present- Contributed to PROCIENCIA-funded project (PE501086701-2024) in precision agriculture and robotics
- Built a data acquisition platform on ROS for a mobile robot equipped with a ZED 2i stereo camera, enabling non-technical users to capture video from field environments
- Led a team of 3 interns building a modular pipeline for preprocessing and labeling
- Managed code versioning and collaboration using GitHub across training and labeling workflows
Computer Vision Intern
Sept 2022 - Feb 2024- Designed and implemented detection and segmentation strategies for crops (blueberries and artichokes) using YOLOv7/v8, Mask R-CNN, and MLPs
- Configured simulation environments with ROS-Noetic, rviz, Gazebo, and ZED cameras, integrating models on a mobile robot with Jetson Xavier
- Collaborated on the redesign of a PPG-based optosensor, implementing digital filters in C++ for Arduino
Research Student
Jul 2020 - Sept 2022- Restored and deployed an IIoT system for an artichoke project, configuring and managing the Linux environment
- Researched state of the art in crop detection and classification, evaluating algorithms such as Mask R-CNN and YOLO
- Managed blueberry image datasets, including labeling with Roboflow
Projects
LabelFlow: Video Annotation Tool
Open-source video annotation tool with motion-aware propagation using optical flow, YOLO re-detection, and region matching. Supports automatic object tracking across frames with persistent identity assignment and bulk operations.
RepositorySignature Verification via Siamese CNNs
Siamese CNN for signature comparison based on learned representations, deployed as API on AWS (Lambda, EC2). Optimized inference using ONNX runtime and tracked experiments with Weights & Biases.
RepositoryML Models Review
Implementation of state-of-the-art Deep Learning models from scratch using PyTorch, focused on image classification and semantic segmentation.
Repository