Samantha Guerriero, Developer in London, United Kingdom
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Samantha Guerriero

Bio

With over 20 data science and AI projects delivered for startups, enterprises, and academia, Sam offers a unique expertise blend as a senior AI consultant skilled in both hands-on engineering work and leadership roles with a special focus on team leading, project management, and thought leadership. By exploring the AI field from diverse perspectives and through varied projects, Sam is interested and committed to developing AI initiatives where growth, impact, and kindness are all at the center.

Portfolio

Freelance Clients
Artificial Intelligence (AI), AIOps, Machine Learning Operations (MLOps)...
Checkout.com
Amazon Web Services (AWS), Snowflake, Data Build Tool (dbt), Dask, Python...
Datatonic
Google Cloud Platform (GCP), TensorFlow, Consulting, Presales, Recruiting...

Experience

  • Computer Vision - 8 years
  • Consulting - 7 years
  • Keras - 7 years
  • Google Cloud Platform (GCP) - 7 years
  • Machine Learning Automation - 4 years
  • Content Writing - 3 years
  • Generative Artificial Intelligence (GenAI) - 1 year
  • Online Course Development - 1 year

Preferred Environment

Linux, MacOS, Google Cloud Platform (GCP), Python, Docker, Amazon Web Services (AWS), Kubernetes, Gemini, OpenAI, LangChain

The most amazing...

...project I've led is a vision model identifying products from in-app images: >95% accuracy, >60% package-free items, improved UX, and lots of plastic saved!

Work Experience

AI Consultant / ML Engineer

2021 - PRESENT
Freelance Clients
  • Delivered >10 AI projects within specified timelines and budgets with measurable impact on increased efficiency, customer acquisition, and cost savings.
  • Maintained successful long-term relationships with a client retention rate of 50%.
  • Participated in webinars and meet-ups as an AI SME consulting for startups and small businesses.
  • Experienced the AI field from varied angles by contributing to technical, marketing, and educational projects as an individual contributor, project manager, advisor, and thought leader.
Technologies: Artificial Intelligence (AI), AIOps, Machine Learning Operations (MLOps), Machine Learning, Data Science, Google Cloud, Amazon Web Services (AWS), Thought Leadership, Advisory, AI Prompts, Prompt Engineering, ChatGPT, Gemini, LangChain, Generative Artificial Intelligence (GenAI), Content Writing, Online Course Development

Senior Machine Learning (MLOps) Engineer

2021 - 2022
Checkout.com
  • Ideated and developed the automated retraining pipeline for the fraud engine model in Airflow.
  • Designed and set up an internal package for machine learning, MLOps, and data functionalities.
  • Introduced a new set of best practices for data, code, and model testing, leading to increased coverage by 50%.
  • Consulted periodically with the data science team on optimization for the current model pipeline.
  • Refactored multiple components of the deployment pipeline—from the feature engineering module to API service—which heavily reduced maintenance and running costs.
Technologies: Amazon Web Services (AWS), Snowflake, Data Build Tool (dbt), Dask, Python, TeamCity, Jenkins, Octopus Deploy, Linux, MacOS, XGBoost, Scikit-learn, Keras, Docker, Machine Learning, Statistical Methods, Database Design, Recruiting, Data Science, Machine Learning Automation, System Design, Cloud, Networking, Kubernetes, SQL, English, Automation, Google Structured Data, Batch Prediction, APIs, Deep Learning, Machine Learning Operations (MLOps), Content Writing, Artificial Intelligence (AI), Pandas, Big Data, Algorithms, Deep Neural Networks (DNNs), Mathematics

Senior Machine Learning Engineer | Acting Head of AI Automation

2018 - 2021
Datatonic
  • Consulted, designed, and delivered DS, ML, and MLOps projects from PoC to production-ready systems with 100 NPS for clients like Realeyes, BT, Vodafone, and Lush.
  • Managed junior team members to set and achieve OKRs, fostering a proactive attitude towards achieving what they enjoy and want to learn.
  • Established the AI automation practice with the head of ML, from offerings and client profiles to strategic and marketing collateral for the internal team, clients, and stakeholders.
  • Cultivated and expanded the technical partnership with Intel through multiple R&D projects, resulting in research pieces with thousands of views online.
  • Initiated, coordinated, and participated in internal initiatives for the team, including all-hands days, Niko-Niko calendar, hiring, surveys, and OKR sessions.
  • Provided AI thought leadership pieces, white papers, talks, and training to practitioners and global leaders on best practices for AI on Google Cloud.
Technologies: Google Cloud Platform (GCP), TensorFlow, Consulting, Presales, Recruiting, Management, Thought Leadership, Computer Vision, Propensity Modeling, Deep Learning, Linux, MacOS, XGBoost, Scikit-learn, Keras, Kubeflow, Python, Docker, Machine Learning, Natural Language Processing (NLP), Statistical Methods, Business Planning, Database Design, Web Scraping, Sentiment Analysis, Data Science, Machine Learning Automation, Google Cloud Machine Learning, System Design, Cloud, Networking, Kubernetes, Cloud Dataflow, Pub/Sub, Google Kubernetes Engine (GKE), Cloud Storage, BigQuery, SQL, English, Automation, Google Structured Data, Batch Prediction, Google Cloud Video API, Google Cloud API, APIs, Object Detection, Data Build Tool (dbt), Dask, Google Cloud, Machine Learning Operations (MLOps), Content Writing, Artificial Intelligence (AI), Recommendation Systems, Pandas, Big Data, Algorithms, Deep Neural Networks (DNNs), Mathematics, Optical Character Recognition (OCR), Blogging, Convolutional Neural Networks (CNNs), Deep & Cross Network (DCN), Embedding Models

Machine Learning Researcher

2017 - 2017
University of Amsterdam
  • Designed the first deep version of NCM in literature, previously considered an impossible task by the community, and further enhanced the classifier with incremental learning and open-set learning techniques.
  • Obtained state-of-the-art accuracy for the NCM and Deep NCM algorithms in multiple scenarios.
  • Performed extensive analysis of state-of-the-art solutions and literature, further progressed by discussions in reading groups beside Ph.D. students.
  • Attended weekly meetings to present deliverables and propose new directions of work.
  • Gathered extensive experience in creating custom models in TensorFlow using graph mode and in Theano, following best practices in the design and finetuning of experiments.
Technologies: Research, Computer Vision, Python, TensorFlow, Deep Learning, Linux, Keras, Machine Learning, Statistical Methods, Mathematics, Web Scraping, Data Science, English, Batch Prediction, Content Writing, Artificial Intelligence (AI), Algorithms, Deep Neural Networks (DNNs), Convolutional Neural Networks (CNNs)

Machine Learning Intern

2015 - 2015
WonderFlow
  • Researched and built a tailored method for automatic polarity tagging of sentences developed in RapidMiner.
  • Guided Wonderflow with the continuance of revenue generating by proposing tailor-built solutions and promoting the business’ technical advancement to investors alongside the founders of the company.
  • Researched and analysed competitors’ techniques and proposed improvements.
  • Reduced the business’ costs by 0.7€/review and optimized the business’ performance by 30 seconds/review, by conceptualizing and developing a new automatic mechanism for the business workflow.
  • Attended events alongside the founders and built relationships with other potential new business partners.
Technologies: Web Scraping, RapidMiner, Natural Language Processing (NLP), Sentiment Analysis, Machine Learning, Statistical Methods, Research, Data Science, English, Batch Prediction, Artificial Intelligence (AI), Algorithms, Mathematics

Experience

MLOps Pipeline Automation with Kubeflow

Supported a global marketing analytics company using computer vision to analyze emotional responses to online ads. Designed and implemented a scalable Kubeflow-based pipeline to automate model training, experiment tracking, and deployment, enabling the client’s ML team to iterate faster and collaborate efficiently across environments.

Predictive Analytics for Brand Purchase Propensity

Built a brand propensity scoring model for one of the UK’s largest retailers to predict which brands customers were most likely to purchase next. The solution combined behavioral, transactional, and demographic data using TensorFlow and other ML frameworks, and was validated through A/B-tested marketing campaigns that boosted engagement with new arrivals.

Object Detection for Automated News Article Retrieval

Developed an automated news retrieval system for a fast-growing marketing and advertising agency. Using TensorFlow Object Detection, the solution analyzed newspaper screenshots to localize headlines and extract article data. Integrated Google Cloud APIs to retrieve source URLs, article images, keywords, and sentiment, enabling efficient content monitoring across multiple media outlets.

Content Writer in Data and AI

Published 90+ in-depth articles and thought-leadership pieces for AI, data, and cloud technology companies. Covered topics such as MLOps, data fabric, ML model governance, LLMs, AI Security, and TensorFlow Serving. Collaborated with SMEs and marketing teams to translate complex ideas into accessible, high-performing content that increased client engagement and brand visibility.

Advisory for Data Science Platform Migration

Advised a data science team on migrating their existing ML infrastructure to Kubeflow. Authored a comprehensive system requirements and architecture document outlining business use cases, functional specifications, and deployment design. Guided the implementation plan for a successful proof of concept delivered within two weeks, while evaluating alternative solutions such as Vertex AI and other managed cloud platforms.

Matching Solution for Hiring Platform

Served as an AI consultant for a startup developing a platform to connect talent with job opportunities. I led the design of the initial matching solution, managed the creation of an MVP using a rule-based approach, and collaborated on UX elements for structured data collection. I also defined a phased roadmap toward integrating deep learning–based matching in future iterations.

Recommender System for an Online Retail Platform

A recommender system built to enhance product personalization on a large eCommerce platform. I developed and trained models on millions of user–item interactions, starting from matrix factorization baselines to advanced deep learning architectures for collaborative filtering. The solution included an automated pipeline covering data preprocessing, model training, and evaluation.

Cloud SQL to BigQuery Migration Pipeline

A financial data pipeline built on Google Cloud Platform. I designed and implemented an MVP to migrate datasets from Cloud SQL to BigQuery using Apache Beam and Dataflow, with full automation through Cloud Composer (Airflow). I also enhanced pipeline efficiency by parallelizing workflows and optimizing schema design to improve speed and reliability.

Education

2015 - 2017

Master's Degree in AI & Robotics

Sapienza - Rome, Italy

2012 - 2015

Bachelor's Degree in Information Technology

RomaTre - Rome, Italy

Certifications

MAY 2022 - PRESENT

Machine Learning Engineering for Production (MLOps)

DeepLearning.AI | via Coursera

NOVEMBER 2020 - NOVEMBER 2022

Google Cloud Certified Professional Machine Learning Engineer

Google Cloud

NOVEMBER 2019 - NOVEMBER 2021

Google Cloud Certified Cloud Architect

Google Cloud

DECEMBER 2018 - DECEMBER 2020

Google Cloud Certified Data Engineer

Google Cloud

JUNE 2011 - PRESENT

Cambridge English: Proficiency (CPE)

University of Cambridge

Skills

Libraries/APIs

TensorFlow, Pandas, XGBoost, Scikit-learn, Keras, Google Cloud Video API, Google Cloud API, Dask, PyTorch

Tools

Jupyter, Amazon SageMaker, 2Checkout, ChatGPT, Cloud Dataflow, Google Kubernetes Engine (GKE), BigQuery, TeamCity, Jenkins, Google AI Platform, Azure Machine Learning, Jira, Apache Airflow, Apache, Google Cloud Composer, Apache Beam, AI Prompts

Languages

Python, SQL, Snowflake, JavaScript

Platforms

Google Cloud Platform (GCP), Kubeflow, Linux, Docker, MacOS, RapidMiner, Kubernetes, Amazon Web Services (AWS), Vertex AI, NVIDIA CUDA

Frameworks

Flask

Paradigms

Database Design, Management, Automation, Agile Software Development, DevOps, Agile, Deep & Cross Network (DCN), Instructional Design

Storage

Google Cloud, PostgreSQL, Amazon FSx

Other

Machine Learning, Computer Vision, Consulting, Thought Leadership, Data Science, Content Writing, Artificial Intelligence (AI), Recommendation Systems, Algorithms, Deep Neural Networks (DNNs), Neural Networks, Presales, Sentiment Analysis, Machine Learning Automation, Google Cloud Machine Learning, Object Detection, Deep Learning, Image Processing, Big Data, Technical Writing, Convolutional Neural Networks (CNNs), Optical Character Recognition (OCR), Image Recognition, Writing & Editing, Blogging, AI Democratization, Llama 3, Online Course Development, Natural Language Processing (NLP), Robotics, Statistical Methods, Mathematics, Business Planning, Economics, Recruiting, Propensity Modeling, Research, Web Scraping, System Design, Cloud, Networking, Pub/Sub, Cloud Storage, English, Google Structured Data, Batch Prediction, APIs, Data Build Tool (dbt), Octopus Deploy, Machine Learning Operations (MLOps), Technical Design, Large Language Models (LLMs), Diffusion Models, Generative Adversarial Networks (GANs), Data Collection, Technical Requirements, User Experience Design, Product Roadmaps, AIOps, Advisory, Retrieval-augmented Generation (RAG), Embedding Models, Matrix Factorization, Feature Engineering, Collaborative Filtering, Model Tuning, Data Engineering, Google Cloud Dataflow, Google BigQuery, Prompt Engineering, Gemini, OpenAI, LangChain, Generative Artificial Intelligence (GenAI), Content Strategy, Amazon Bedrock, AI Security, AI Ethics, Hardware Selection, Quantization, Neural Network Pruning, Hardawre Configuration, Curriculum Design, AI Education, Agentic AI

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