Jesús is available for hire
Hire JesúsJesús Martínez
Verified Expert in Engineering
AI Engineer and Developer
Bogotá - Bogota, Colombia
Toptal member since November 11, 2019
Bio
Jesús is an AI and back-end engineer with 14 years building software and 10 years shipping production ML systems. He specializes in LLM applications, AI agents, workflow automation, and scalable back-end services. From prototyping NLP models to deploying multi-agent platforms, he delivers end-to-end solutions using Python, modern AI frameworks (OpenAI, Anthropic, open-source LLMs), RAG architectures, and cloud infrastructure, helping clients move fast without sacrificing quality.
Portfolio
DataSmarts
Scala, Java, TensorFlow, AutoML, Scikit-learn, NumPy, Pandas, PyTorch, Python...
Token Land, LLC
Artificial Intelligence (AI), AI Architecture, Large Language Models (LLMs)...
JIA NOMADS LIMITED
Python, LangChain, Knowledge Graphs, n8n, Automation, OpenAI, Claude, Gemini...
Experience
- Machine Learning - 10 years
- Python - 10 years
- Natural Language Processing (NLP) - 5 years
- LangChain - 4 years
- TensorFlow - 3 years
- Deep Learning - 2 years
- n8n - 2 years
- DeepSeek - 1 year
Work Experience
Founder | AI Consultant
2017 - PRESENT
DataSmarts
- Helped create Knowledge DBs using Python, RAG AI, and Pinecone to analyze historical data and present tailored dashboards.
- Published weekly blog articles in Spanish, elucidating machine learning and computer vision concepts at both low and high levels.
- Produced weekly Spanish video tutorials on prominent computer vision and machine learning topics, featuring comprehensive step-by-step instructions and explanations.
- Developed and openly shared the source code for numerous computer vision projects, accompanied by comprehensive comments and instructions for execution and customization.
- Authored an Amazon best-selling book on computer vision recipes using TensorFlow 2 in partnership with Packt.
Technologies: Scala, Java, TensorFlow, AutoML, Scikit-learn, NumPy, Pandas, PyTorch, Python, Keras, Machine Learning, Artificial Intelligence (AI), ChatGPT, OpenAI GPT-4 API, SQL, Language Models, Neural Networks, Databases, Meta Llama, n8n, Pinecone, Architecture, Microservices, Automation, Agentic AI, Anthropic, Agentic Frameworks, Prompt Engineering, Vector Databases, LLM Integration, Observability, Model Evaluation, RAG Architecture, APIs, Conversational AI, Node.js, Workflow Automation, LangSmith, AI Agent Orchestration, AI Voice Agents, CRM, AI Architecture, AI Integration, Claude Code, Browser Automation, Playwright, Whisper, Interviewing, Dashboards
AI Architect
2026 - 2026
Token Land, LLC
- Shipped a public multilingual legal Q&A platform that, per client reporting, turned about 100 visitor questions into 33 booked consultations and 5 signed matters at around $5,000 each in its first 2.5 weeks live.
- Led architecture and delivery as sole engineer for two legal AI products across four repositories, both live in production within four months, spanning three Python services, a TypeScript API, and a React review interface.
- Encoded the client's written AI conduct rules as enforced system behavior: mandatory disclaimers, no eligibility determinations or outcome predictions, and evaluation suites grading outputs against attorney-authored ideal answers.
- Designed a multi-tenant retrieval platform for institutional handover, with append-only audit logs under compliance retention, tenant isolation enforced as a filter floor, and three vector store backends behind one vendor-neutral export.
- Built an expert curation pipeline that captured the attorney's judgment at scale, then fed the selected gold answers back into live inference as retrieved few-shot examples.
- Owned deployment and production operations across Render, Supabase, and AWS, and defined the API contracts that two external front-end teams built against.
Technologies: Artificial Intelligence (AI), AI Architecture, Large Language Models (LLMs), AI Chatbots, Retrieval-augmented Generation (RAG), Architecture, Technical Leadership, Prompt Engineering, Amazon Web Services (AWS), Python, OpenAI, Claude, Gemini, Agentic AI, Agentic Frameworks, AI Agent Orchestration, AI Agents, AI Integration, Anthropic, Claude Code, Claude API, APIs, ChatGPT, Whisper, Dashboards
AI Solutions Architect
2024 - 2026
JIA NOMADS LIMITED
- Architected and developed an AI-powered email processing pipeline that automated inbox triage for 50+ users, classifying and summarizing 300+ emails daily with 80% accuracy and 85%+ user satisfaction.
- Built a multi-stage NLP pipeline using GPT-4 and Gemini 1.5 Pro to classify emails, extract actionable tasks, generate thread summaries, and produce daily/weekly reports stored in Supabase.
- Led technical migration from Make to Python and subsequently to self-hosted n8n, reducing operational costs from $500/month to $50/month while maintaining non-technical stakeholder visibility into system architecture.
- Owned 95% of back-end and AI development, collaborating with CTO on product direction and coordinating with beta testers to validate system behavior.
- Designed and built a multi-tenant, conversational AI agent that managed Google Calendar operations across Signal, Slack, WhatsApp, and Telegram with 20+ active users executing dozens of calendar operations daily.
- Integrated Google Calendar API, Tavily web search, and Google Maps API to enable natural language event scheduling, including venue lookup and intelligent time/location resolution.
- Implemented platform-agnostic messaging abstraction layer to normalize incompatible channel APIs into a unified conversational interface while maintaining per-channel isolation.
- Migrated system from n8n to Python, reducing average agent response time from 2-3 minutes to under 20 seconds and enabling complex multi-step workflows.
Technologies: Python, LangChain, Knowledge Graphs, n8n, Automation, OpenAI, Claude, Gemini, Gmail API, Google Maps API, Neo4j, JavaScript, Supabase, SQL, PostgreSQL, Agentic AI, Telegram Bot API, Slack API, Langfuse, Redis, MongoDB, LangGraph, AI Agents, Anthropic, Agentic Frameworks, Prompt Engineering, Vector Databases, LLM Integration, Observability, Model Evaluation, RAG Architecture, APIs, Conversational AI, Node.js, Workflow Automation, AI Agent Orchestration, AI Voice Agents, AI Architecture, AI Integration, Claude Code, ChatGPT, Whisper
AI Solutions Architect
2025 - 2025
Crescendo Creative LLC
- Architected and deployed Forge, a multi-agent AI platform with eight specialized assistants for business planning, asset generation, social media data collection, and workflow automation, replacing manual processes for a political marketing agency.
- Built 10+ N8N workflows with complex sub-workflow orchestration, enabling a master agent to parse user requests and delegate tasks autonomously across specialized agents via Slack.
- Integrated multiple LLM providers (GPT-4.1, Claude 4.5 Sonnet, Gemini 2.5 Pro) via OpenRouter, selecting models based on task requirements to balance cost, latency, and output quality.
- Implemented a Supabase back end for conversation history, response caching, and asset storage, ensuring state persistence and context continuity across agent interactions.
- Solved integration challenges, including API rate limiting across social platforms, stateful handoffs between agents, and unofficial API workarounds for Midjourney and Kling asset generation.
- Delivered production system now actively used by a 3-person team, consolidating 6+ external tools into a single Slack-based interface and reducing context-switching overhead by an estimated 3–5 hours per user per week.
Technologies: Artificial Intelligence (AI), Python, Machine Learning, Natural Language Processing (NLP), n8n, Automation, Computer Vision, Large Language Models (LLMs), Claude, OpenAI, Gemini, LangGraph, Agentic AI, AI Agents, Anthropic, Agentic Frameworks, Prompt Engineering, Vector Databases, LLM Integration, Observability, Model Evaluation, RAG Architecture, Model Context Protocol (MCP), APIs, Conversational AI, Workflow Automation, AI Agent Orchestration, AI Voice Agents, CRM, AI Architecture, AI Integration, Claude Code, Whisper
AI Developer
2025 - 2025
United Claims Specialists, LLC
- Automated daily and weekly lead follow-up tracking for 12+ executives managing hundreds of leads per week using n8n and AI-powered report generation, reducing manual report compilation time from 3-5 hours per week to under two minutes per run.
- Built custom Google Sheets dashboards using n8n and Google Apps Script to consolidate nightly RingCentral phone data (call duration, timing, outcomes), replacing manual monthly reporting with daily-refreshed performance visibility for management.
- Deployed five production n8n workflows integrating Google Sheets (used as CRM), RingCentral APIs, and AI validation to enforce business rules and generate actionable reports, with all automations remaining in active use after contract completion.
- Integrated n8n workflows with existing Zapier infrastructure to sync internal contact data across 12 executives, ensuring consistent lead and contact information across automation pipelines.
- Built and deployed a RAG-based AI chatbot for company-wide employee access, enabling self-service answers to process and policy questions from internal documentation, and created video documentation for technical handoff and end-user training.
Technologies: Artificial Intelligence (AI), Python, Large Language Models (LLMs), OpenAI, Retrieval-augmented Generation (RAG), Natural Language Processing (NLP), API Integration, n8n, Automation, Claude API, Claude, Zapier, Google Apps Script, Agentic AI, AI Agents, Anthropic, Agentic Frameworks, Prompt Engineering, LLM Integration, Observability, Model Evaluation, RAG Architecture, Model Context Protocol (MCP), APIs, Conversational AI, Workflow Automation, AI Agent Orchestration, AI Voice Agents, CRM, AI Architecture, AI Integration, Whisper, Dashboards
AI Engineer
2024 - 2025
Padrino's Restaurants Inc
- Architected and deployed a bilingual (English/Spanish) AI assistant across 5 restaurant locations, handling 20+ daily staff queries with 90%+ resolution rate and reducing manager interruptions by approximately 75%.
- Built a voice and text-enabled chatbot using Voiceflow and deployed it on a custom web platform developed with Bolt.new, enabling kitchen staff and waiters to access recipes, SOPs, contacts, and operational procedures on demand.
- Designed and implemented an automated knowledge base sync pipeline using n8n to pull hundreds of multimedia records (videos, images, text) from Airtable daily, ensuring staff access to current recipes and standard operating procedures.
- Delivered the complete solution in one month as sole architect and developer, working directly with the CEO to address language barriers for non-English-speaking staff at a Cuban restaurant.
Technologies: Artificial Intelligence (AI), Machine Learning, Natural Language Processing (NLP), Large Language Models (LLMs), Voiceflow, n8n, Automation, Chatbots, OpenAI, Claude, JavaScript, Agentic AI, AI Agents, Anthropic, Agentic Frameworks, Prompt Engineering, LLM Integration, Observability, APIs, Conversational AI, Workflow Automation, AI Agent Orchestration, AI Voice Agents, AI Architecture, AI Integration
LLM Engineer (Python + Pinecone + RAG technologies)
2024 - 2025
Cortado, Inc.
- Enhanced the state-of-the-art LLM-powered AI agent significantly for the property rental industry. Also implemented a DB using Pinecone for data consolidation.
- Increased the efficiency of the data ingestion pipeline, resulting in lower costs and better user experience.
- Helped plan, design, and execute the migration from a monolithic architecture to a distributed event-based one.
Technologies: Artificial Intelligence (AI), Retrieval-augmented Generation (RAG), Large Language Models (LLMs), Machine Learning Operations (MLOps), LangChain, LlamaIndex, Vector Databases, Amazon SageMaker, DSPy, Real Estate, Meta Llama, n8n, Python, Pinecone, Architecture, Amazon Web Services (AWS), Microservices, Automation, Agentic AI, AI Agents, Anthropic, Agentic Frameworks, Prompt Engineering, RAG Architecture, APIs, Node.js, Workflow Automation, LangSmith, AI Agent Orchestration, AI Architecture, AI Integration
Senior Data Engineer
2024 - 2024
Komorebi Investment Pty Ltd
- Built a natural language database query agent using Python and LangChain that reduced safari planning time by 20% by enabling 3+ agents to retrieve itinerary templates, pricing, availability, and vendor data from PostgreSQL and unstructured sources.
- Designed and deployed a Streamlit-based interface that queried tens of relational tables with thousands of records, allowing safari planners to generate custom proposals for high-net-worth clients across Nairobi and other African destinations.
- Implemented SQL generation guardrails, including query validation, schema enforcement, and error handling, to ensure safe and accurate interactions with complex relational data structures.
- Delivered the end-to-end solution as sole engineer in six weeks, collaborating with CTO and stakeholders to scope requirements and validate agent performance in a production pilot environment.
Technologies: Data Science, ETL, Databases, ETL Tools, Data Cleaning, Data Pipelines, Large Language Models (LLMs), ChatGPT, OpenAI, Prompt Engineering, Optical Character Recognition (OCR), AI Agent Orchestration, AI Architecture
Senior Data Engineer
2024 - 2024
Komorebi Investment Pty Ltd
- Developed efficient ETL processes to ensure the AI's data was always fresh and relevant, enhancing its ability to provide accurate and contextually relevant information.
- Built AI assistants using retrieval-augmented generation (RAG) techniques, integrating large language models like GPT-4-turbo with vector databases such as ChromaDB and Pinecone.
- Worked with a South African company to develop AI assistants using retrieval-augmented generation (RAG) techniques, integrating large language models like GPT-4-Turbo with vector databases such as ChromaDB and Pinecone.
Technologies: Data Science, ETL, Databases, ETL Tools, Data Cleaning, Data Pipelines, Meta Llama, Architecture, Microservices, AI Architecture
Data Scientist | ML Engineer
2023 - 2024
ContractPod Technologies Limited
- Developed and fine-tuned advanced models for tasks such as document classification, summarization, information discovery, and risk analysis using models like GPT-4, Llama 3, Gemini 1.5, and Mistral.
- Fine-tuned open-source models like Llama 3 to match the performance of proprietary models such as GPT-4, addressing privacy concerns and ensuring data security without compromising performance.
- Optimized inference costs by improving prompt efficiency and reducing LLM calls, enhancing both the privacy and performance of AI models and resulting in substantial cost savings.
Technologies: Natural Language Processing (NLP), Data Science, LSTM, Machine Learning, TensorFlow, BERT, Python, OpenAI, Llama 2, Reinforcement Learning, Large Language Models (LLMs), Language Models, ChatGPT, Falcon, PEFT, Meta Llama, Hugging Face, Microservices, Automation, AI Agents, Prompt Engineering, Optical Character Recognition (OCR), AI Agent Orchestration, AI Architecture
AI Engineer | Machine Learning Engineer
2017 - 2023
Mahisoft
- Engineered and optimized named entity recognition model using NLTK, scikit-learn, and SpaCy. This enhanced solution enhanced simplicity, speed, and reliability, successfully replacing the previous production model.
- Designed and developed a sophisticated prototype utilizing computer vision and deep learning techniques, seamlessly integrated into the accompanying software suite of cameras manufactured by a renowned Japanese electronics company.
- Automated the integration of our systems with various third-party machine learning solutions, including Google's AutoML. Simplified the process, enhancing efficiency and enabling seamless adoption of advanced technologies.
- Developed a data ingestion pipeline that breaks down legal documents stored in diverse formats, generating multiple artifacts to facilitate future and further experimentation.
- Developed a Java and Spring Boot-based RESTful framework to train NLP models for tasks like text classification, clustering, and named entity recognition. This sped up model development, resulting in improved performance and scalability.
Technologies: Natural Language Toolkit (NLTK), Computer Vision, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), AutoML, Pandas, Keras, NumPy, Scikit-learn, TensorFlow, Java, Spring Boot, Python, Machine Learning, PySpark, Generative Pre-trained Transformer 3 (GPT-3), Artificial Intelligence (AI), OpenAI, ChatGPT, OpenAI GPT-4 API, OpenAI GPT-3 API, SQL, Language Models, Neural Networks, Azure, Data Pipelines, ETL, Databases, Hugging Face, Amazon Web Services (AWS), Microservices, APIs, Optical Character Recognition (OCR), AI Agent Orchestration, AI Architecture, Interviewing
Machine Learning Engineer
2019 - 2022
Blue Orange Digital
- Implemented the data model of an NLP-powered application to automatically tag topics of interest in pharmaceutical documents, supported by a combination of key terms and machine learning, surpassing the accuracy of human reviewers by 10%.
- Implemented a forecasting model using SARIMAX and traditional machine learning to help the sales team of an important pharmaceutical company project quarterly earnings.
- Created a computer vision solution to correct poor-resolution PDF scans, which resulted in a higher-quality text extraction through OCR.
- Maintained a Spark-powered data aggregation platform to consolidate information about high-profile brokers used by one of the biggest investment firms in the United States.
Technologies: Scikit-learn, TensorFlow, Natural Language Toolkit (NLTK), OpenCV, Data Science, Computer Vision, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Python, Machine Learning, PySpark, Artificial Intelligence (AI), ChatGPT, OpenAI GPT-4 API, OpenAI GPT-3 API, SQL, Language Models, Neural Networks, Data Pipelines, ETL, Databases, Microservices, APIs
Senior Software Engineer
2017 - 2020
Mahisoft
- Developed a customizable password policies feature in an authentication microservice that is being used in the production environment of four major clients.
- Developed and co-designed a flexible, generic, multi-channel notifications microservice that was adopted in multiple clients' production systems.
- Worked intensely on the four important microservices of the company's flagship product, which contributed to the acquisition of several new, big, and important clients.
- Created written and multimedia documentation of multiple parts of the internal architecture of our main product, which reduced the ramp-up time of new hires by 50%.
- Provided intensive and detailed training for a new team member, which resulted in a seamless role transition in a core project for a key client.
- Imparted a series of workshops focused on the development of machine learning solutions using JVM technologies.
- Optimized the database queries of a major multi-billion dollar client that helped to reduce the runtime of a critical process from two hours to nine minutes, on average.
Technologies: Elasticsearch, Apache Kafka, MySQL, Go, Spring Boot, Docker, Java, JavaScript, SQL, ETL, Databases, Microservices
Computer Vision Engineer
2019 - 2019
Freelance
- Developed a people counter algorithm that works on RGB data from cameras installed in zenithal position, which is now being used in multiple venues throughout Colombia.
- Built a height estimator based on depth sensor information which was used to prevent the access of underage people to age-restricted areas. This solution is deployed in more than ten locations in Colombia.
- Created an algorithm to extract, correct, and merge data from an RGB-D camera, which reduced the setup and familiarization time to this particular brand of cameras.
Technologies: NumPy, Scikit-learn, Keras, Python, OpenCV, Machine Learning, Databases, Microservices, APIs, Optical Character Recognition (OCR)
Back-end Engineer
2016 - 2017
Wivo
- Worked on the development of a new version of the company's main product, replacing the monolithic architecture of the application with a microservices oriented one, which reduced the maintenance time by 50%.
- Participated in the screening and interview process of dozens of potential candidates, which resulted in the hiring of four new, highly-skilled key members for the back end, front end, and infrastructure teams.
- Designed a sandbox-like architecture of microservices based on Docker and configurable templates that allowed the company to set up systems for new clients in a fraction of the time that was needed before.
- Documented the most relevant parts of the back-end ecosystem, which greatly improved the effectiveness and productiveness of the team.
Technologies: GraphQL, Python, MongoDB, Redis, PostgreSQL, Akka, Scala, Docker, Clojure, JavaScript, Microservices, APIs, Interviewing
Senior Software Developer
2015 - 2016
Mesfix
- Migrated the previous monolithic architecture to a microservices-oriented one, which increased the scalability, response time, and overall quality of the company's product.
- Scaled and maintained the CI, test, development, and production environments.
- Led a team of three members focused on back-end development endeavors.
- Imparted a series of workshops focused on learning quickly the basics of Python, which increased the team's productivity.
Technologies: Software Engineering, Java, MongoDB, Jenkins, RabbitMQ, Scala, PostgreSQL, Python, JavaScript, Microservices, APIs
Software Engineer
2014 - 2015
S4N
- Participated in the development of the flagship product of a very important client, consisting of a secure, cloud-based, vault-like storage system.
- Implemented an online, stateful onboarding form for the biggest insurance company in Colombia (Sura), which reduced the time taken by the process from one week. on average, to only three hours.
- Fostered a culture of functional programming based solutions in the company, through a series of educational, hands-on workshops.
Technologies: Software Engineering, Java, MongoDB, PostgreSQL, Akka, Scala, JavaScript, Microservices, APIs
Project History
Virtual Concierge for Lifestyle Magazine
https://nande.co/Designed and implemented a sophisticated chatbot solution for a renowned lifestyle online magazine, serving as a virtual concierge to cater to user needs. The primary objective was to curate custom itineraries and provide comprehensive activity summaries for various metropolitan areas, including Chicago, based on user-supplied preferences and parameters.
This project's successful development and deployment resulted in a major increase in user engagement and satisfaction.
This project's successful development and deployment resulted in a major increase in user engagement and satisfaction.
Vehicle Detector
https://github.com/jesus-a-martinez-v/vehicle-detectionI created an advanced algorithm for car detection in video streams, capable of accurately identifying vehicles of varying sizes and distances. The algorithm leverages a combination of traditional computer vision techniques, including Histogram of Oriented Gradients, and machine learning algorithms, such as Linear SVC. The algorithm employs a sliding window approach to enhance precision and mitigate false positives and duplicate detections and incorporates a configurable heatmap based on the last N frames.
Lane Lines Finder
https://github.com/jesus-a-martinez-v/advanced-lane-linesDeveloped a robust pipeline utilizing sophisticated computer vision techniques to accurately track lane lines on road surfaces and provide essential curvature information.
The pipeline integrates cutting-edge methodologies, including perspective transform, camera calibration, edge detection, Gaussian blurring, and polynomial fitting, to achieve precise lane line detection and analysis.
The pipeline integrates cutting-edge methodologies, including perspective transform, camera calibration, edge detection, Gaussian blurring, and polynomial fitting, to achieve precise lane line detection and analysis.
Education
2008 - 2013
Bachelor's Degree in Computer Engineering
Universidad Simón Bolívar - Caracas, Venezuela
Certifications
SEPTEMBER 2018 - PRESENT
Computer Vision Nanodegree
Udacity
FEBRUARY 2018 - PRESENT
Deep Learning Specialization
Deeplearning.ai via Coursera
JANUARY 2018 - PRESENT
Machine Learning Engineer Nanodegree
Udacity
JUNE 2017 - PRESENT
Deep Learning Engineer Nanodegree
Udacity
Skills
Libraries/APIs
Keras, LSTM, Node.js, Scikit-learn, NumPy, Pandas, OpenCV, Natural Language Toolkit (NLTK), TensorFlow, Playwright, PyTorch, PySpark, Hugging Face Transformers, Claude API, Gmail API, Google Maps API, Telegram Bot API, Slack API
Tools
ChatGPT, n8n, Claude, Claude Code, Whisper, AutoML, PyCharm, RabbitMQ, Jenkins, IntelliJ IDEA, Scikit-image, Amazon SageMaker, DeepSeek, Zapier
Languages
Python, Java, JavaScript, SQL, Scala, Clojure, GraphQL, Go, Python 3, Falcon, Google Apps Script
Frameworks
Agentic Frameworks, Spring Boot, LangGraph, Akka, Spark, LlamaIndex, DSPy
Paradigms
ETL, Microservices, Automation, Functional Programming, Model Context Protocol (MCP), REST
Platforms
Langfuse, Linux, Amazon Web Services (AWS), LangSmith, Docker, Apache Kafka, MacOS, Azure, Voiceflow
Storage
Data Pipelines, Databases, MySQL, PostgreSQL, Redis, Elasticsearch, MongoDB, NoSQL, Neo4j
Other
Machine Learning, Software Engineering, Natural Language Processing (NLP), Data Science, Artificial Intelligence (AI), OpenAI, Neural Networks, Large Language Models (LLMs), Retrieval-augmented Generation (RAG), LangChain, Vector Databases, Meta Llama, Architecture, Gemini, Agentic AI, AI Agents, Anthropic, Prompt Engineering, LLM Integration, Observability, Model Evaluation, RAG Architecture, APIs, Conversational AI, Workflow Automation, AI Agent Orchestration, AI Voice Agents, AI Architecture, AI Integration, Interviewing, Dashboards, Computer Vision, Deep Learning, Generative Pre-trained Transformers (GPT), Generative Pre-trained Transformer 3 (GPT-3), OpenAI GPT-4 API, OpenAI GPT-3 API, Language Models, Hugging Face, Optical Character Recognition (OCR), CRM, Browser Automation, Chatbots, Generative Design, FastAPI, BERT, Llama 2, Reinforcement Learning, PEFT, ETL Tools, Data Cleaning, Machine Learning Operations (MLOps), Real Estate, Pinecone, Computer Engineering, Algorithms, API Integration, Knowledge Graphs, Supabase, AI Chatbots, Technical Leadership
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