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 blog articles, exercising, and being with family and friends.

If I'm interested in something, you might find me writing about it on Medium.

Machine Learning & Computer Vision Engineer

City: Rome, Italy

I currently have 3 years of experience working as a Machine Learning Engineer.

I have a track record of 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

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"

MOOCs & Certifications

Cloud Certifications

2024

Google Cloud Certified - Professional Cloud Architect

2023

Google Cloud Certified - Professional Cloud Machine Learning Engineer

Coursera & DeepLearning.ai

2020-2022

Relevant coursework:

Deep Learning Specialization Neural Networks, hyperparameters tuning and optimization, CNNs, Sequence models.

MLOps: Data pipelines, modelling workflows and data drifts, deployment and monitoring in production environments.

Tensorflow, advanced techniques: custom models, multi-task models, advanced computer vision, generative deep learning.

Skills

Languages

Python, Golang, SQL, C++, MATLAB

ML stack

Pytorch, Tensorflow/Keras, JAX, Scikit-learn, OpenCV, Transformers, SciPy, Pandas, Numpy, Matplotlib, Seaborn, Streamlit, NLTK, SpaCy

Software engineering stack

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

Professional Experience

Advanced Machine Learning Engineer

2022 - Present

Promoted to Advanced Machine Learning Engineer (Sept. 2024)

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

Architected and implemented a Google Cloud-based video processing pipeline, leveraging computer vision and audio analysis to distill petabytes of sports event footage. Developed algorithms to identify and extract the most relevant scenes based on sport-specific criteria, achieving 40-70% storage reduction and resulting in millions of dollars in cost savings.
Designed and implemented a GenAI photobooth web application that transforms user images based on custom text prompts. The solution leverages advanced deep learning models and diffusion-based algorithms for text-to-image and image-to-image transformations. The webapp was showcased at the 2024 BMW Open in Munich and Dreamforce 2024 in San Francisco.
Designed and integrated custom computer vision algorithms for a quadruped robot, optimizing for its specific hardware constraints. Implemented real-time object detection, maintenance panel monitoring, and anomaly detection capabilities, expanding the robot's potential for autonomous inspection and predictive maintenance.

Machine Learning Engineer

2021 - 2022

IPS Intelligence S.p.A, Aprilia, Italy

Engineered a high-accuracy facial recognition and analysis system to discern ethnicity, age, and gender. Leveraged deep learning, transformer-based architectures and weight quantization techniques to ensure high efficiency.
Developed a SAR (Synthetic Aperture Radar) image processing pipeline for maritime intelligence. Implemented advanced machine learning algorithms for vessel tracking and anomaly detection, facilitating rapid identification of potential threats and unusual vessel behaviors.

Computer Vision Developer

2021

C.Ser.Mac AI laboratory, Latina, Italy

Developed a real-time monitoring system using object detection for people, animals, and vehicles.
Implemented a Deep Learning vision system to assess small fruit quality, improving efficiency and accuracy through detection, segmentation and tracking algorithms.