You will get resumes processing via my custom AI processing sofware done for you.

Gabriele M.Status: Offline
Gabriele M.

Let a pro handle the details

Buy Data Entry & Cleaning services from Gabriele, priced and ready to go.
Gabriele M.Status: Offline
Gabriele M.

Let a pro handle the details

Buy Data Entry & Cleaning services from Gabriele, priced and ready to go.

Project details

CV Bam Bam is an AI hiring assistant that reads a stack of resumes and ranks candidates by how well they actually fit a role — not just by keyword overlap. It parses messy PDF and Word CVs into clean structured data, then uses semantic search to match each candidate against the job description, so a "software engineer" still surfaces for a "developer" opening. What sets it apart is genuine fit-scoring over surface matching, plus a done-for-you workflow: you send resumes and a job description, and get back a ranked shortlist in minutes. Screening that took hours becomes consistent, unbiased, and instant.
Data Tool
Python
What's included
Service Tiers Starter
$30
Standard
$50
Advanced
$100
Delivery Time 1 day 2 days 3 days
Number of Revisions
111
Gabriele M.Status: Offline

About Gabriele

Gabriele M.Status: Offline
London, United Kingdom - 7:14 pm local time
LLM & AI Engineer — RAG, Fine-Tuning & Production Deployment

I build and ship AI systems that solve real business problems — not notebooks that never leave the lab. Over the past two years I've deployed RAG assistants, fine-tuned LLMs and diffusion models, and architected a multi-model inference platform running on dual NVIDIA RTX 8000 GPUs, serving LLM, image, and embedding APIs through FastAPI.

What I can do for you:

• **RAG systems** — document ingestion, chunking, embeddings, vector search (pgvector, Chroma, FAISS), and grounded answers with citations. Built for the University of Milan and shipped in production products.
• **LLM fine-tuning & evaluation** — parameter-efficient fine-tuning, MoE architectures, and evaluation harnesses that keep quality measurable, backed by an MSc thesis on lightweight LLM fine-tuning.
• **Agentic workflows** — autonomous agents that reason, plan, and call tools, with human-in-the-loop checkpoints where control matters.
• **Production deployment** — FastAPI backends, Docker, CI/CD, and cloud (AWS, GCP) so what I build stays reliable once it's live.

Before engineering, I spent 15 years founding and running my own companies — so I understand that code only matters if it moves a business outcome. I'll tell you when a simpler solution beats a fancier one, and I explain technical trade-offs in plain language.

MSc in Data Science (Birkbeck, University of London). Fluent in English, Italian, and French.

If you're building something with LLMs, RAG, or AI agents and want it shipped properly, let's talk.



Steps for completing your project

After purchasing the project, send requirements so Gabriele can start the project.

Delivery time starts when Gabriele receives requirements from you.

Gabriele works on your project following the steps below.

Revisions may occur after the delivery date.

process your resume and rank them according to the job description

Review the work, release payment, and leave feedback to Gabriele.