Alessandro Lamberti

About

I'm a Machine Learning and Computer Vision Engineer, with a background in Telecommunication engineering.

Being a curious guy, I do my best every week to learn something new and to keep myself up to speed with the latest news and technologies.

On a more personal note, I like talking to people, writing The Caffeinated Engineer, exercising, and being with family and friends.

Machine Learning & Computer Vision Engineer

City: Rome, Italy

I currently have 4+ years of experience working as a Machine Learning Engineer.

I have a track record of designing, building and deploying machine learning systems, focusing on both computer vision and natural language processing. My toolkit is rich with industry-standard technologies, including Python, GCP, AWS, Docker, PyTorch, and TensorFlow, which I use to write clean, maintainable code that's ready for production environments.

Throughout my career, I have taken machine learning projects from the drawing board to full-scale operation. My role often spans the entire project lifecycle—defining goals, implementing strategies, and leading the transition from development to production.

Resume

Education

Degree in Telecommunications Engineering

2024

La Sapienza - Rome, Italy

Relevant coursework:
Multi-variables calculus, Geometry and Linear algebra, Physics, Computer Science, Electromagnetic fields. Graphs theory, Mathematical methods for information engineering. Signals and data transmission, Internet and Networking, GPS and radar localization.

Thesis: "Edge Learning in 6G Networks: The Impact of Split Learning on Edge Computing"

Skills & Personal Development

Languages

Python, Golang, SQL, C++, MATLAB

ML stack

Pytorch, Tensorflow/Keras, Scikit-learn, OpenCV, Transformers, SciPy, TensorRT, ONNX

Software engineering stack

Docker, AWS, Google Cloud, FastAPI, Flask, ROS2, Git

Certifications

Google Cloud Certified - Professional Cloud Architect
Google Cloud Certified - Professional Cloud Machine Learning Engineer

MOOCs

Deep Learning, MLOps, Tensorflow specializations (Coursera)

Professional Experience

Advanced Machine Learning Engineer

2022 - Present

Promoted to Advanced Machine Learning Engineer (Sept. 2024)

NTT DATA Italia S.p.A, Rome, Italy

Led the end-to-end design and development of a distributed, microservices-based real-time video analysis framework. My responsibilities included defining the architecture to ensure low-latency and high scalability, managing multi-source ingestion, and orchestrating asynchronous tasks with worker pools. Coordinated a team of 2 engineers and established project best practices.
Architected and owned the technical roadmap for Computer Vision solutions for automated inspection using drones and quadruped robots. I designed a pub/sub model architecture integrated with the ROS 2 framework for robotic control, for parallel processing of multiple video feeds and optimized object/anomaly detection models for deployment on resource-constrained edge devices.
Engineered a strategic Google Cloud project for sports footage analysis, designing a video processing pipeline that achieved 40-70% in storage cost optimization. This was accomplished by creating custom ML algorithms for intelligent content filtering and scene extraction.
Led the development and deployment of a production-grade Generative AI application (photobooth) using diffusion models. I ensured its reliability and scalability for thousands of users at high-profile international events, including the BMW Open and Dreamforce 2024, managing the entire lifecycle from concept to production.

Machine Learning Engineer

2021 - 2022

IPS Intelligence S.p.A, Aprilia, Italy

Engineered a high-performance facial recognition and analysis system using Transformer architectures. I implemented weight quantization techniques to optimize inference performance and deployed the system as scalable microservices with REST APIs, enabling real-time demographic attribute detection.
Built an end-to-end pipeline for Synthetic Aperture Radar (SAR) imagery analysis, integrating deep learning models for vessel tracking and behavioral anomaly detection to provide critical maritime intelligence.

Computer Vision Developer

2021

C.Ser.Mac AI laboratory, Latina, Italy

Implemented end-to-end Deep Learning vision systems for automated fruit quality assessment and real-time security monitoring using object detection, tracking and segmentation algorithms