Benito Martin

Data Scientist

https://talent.gravityer.com/benito-martin

😎 AI Engineer

AI Echoes

Key Strengths

Extensive personal project experience in Retrieval-Augmented Generation (RAG) systems, multi-agent AI, and LLM observability.
Demonstrated proficiency in Python, Docker, Makefile, and Shell scripting, indicating strong MLOps and deployment capabilities.
Experience with various vector databases (Qdrant) and cloud platforms (AWS) for RAG implementations.
Projects like 'biomedical-graphrag' and 'mlops-databricks-credit-default' show application of data science in specific domains.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's profile shows a strong inclination towards personal projects, particularly in the rapidly evolving field of LLMs and RAG. This indicates a proactive, self-driven individual with a passion for cutting-edge AI technologies. However, the lack of diverse professional experience (only one current role listed with no details) and limited information on team-based projects makes it difficult to fully assess cultural fit. The focus on personal projects suggests a strong individual contributor, but collaboration and broader organizational fit require further evaluation.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The candidate's profile primarily highlights technical project work without details on collaboration, problem-solving approaches, or communication styles.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

biomedical-graphrag

October 11, 2025 – Present

A comprehensive GraphRAG (Graph Retrieval-Augmented Generation) system designed for biomedical research

View Project

substack-newsletters-search-course

September 26, 2025 – Present

Production RAG System Course

View Project

github-issues-multiagent-intelligence

June 17, 2025 – August 5, 2025

Agentic Github Issues Retrieval on Kubernetes

View Project

llm-observability-opik

May 31, 2025 – June 19, 2025

LLM Evaluation and Observability System for Football Content

View Project

multiagent-langgraph-circleci

March 16, 2025 – June 14, 2025

Collaborative Multi-Agent AI System with LangGraph

View Project

mlops-databricks-credit-default

November 25, 2024 – November 29, 2024

Financial Risk Assessment System

View Project

multimodal-llm-pymupdf4llm

October 4, 2024 – October 4, 2024

Multimodal RAG with PyMuPDF

View Project

multimodal-youtube-recipes

July 11, 2024 – July 11, 2024

YouTube-Based Multimodal Recipe Recommender

View Project

rag-aws-qdrant

June 16, 2024 – June 29, 2024

Academic Paper Q&A with Serverless RAG

View Project

crewai-rag-langchain-qdrant

May 19, 2024 – May 19, 2024

Collaborative Multi-Agent RAG with CrewAI

View Project

Key Strengths

Extensive personal project experience in Retrieval-Augmented Generation (RAG) systems, multi-agent AI, and LLM observability.
Demonstrated proficiency in Python, Docker, Makefile, and Shell scripting, indicating strong MLOps and deployment capabilities.
Experience with various vector databases (Qdrant) and cloud platforms (AWS) for RAG implementations.
Projects like 'biomedical-graphrag' and 'mlops-databricks-credit-default' show application of data science in specific domains.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Benito Martin

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit