Verified Expert in Engineering
Machine Learning Developer
Sam is a bilingual senior machine learning engineer with a background in AI and robotics and a passion for driving innovation. She dedicated the past five years to exploring the best ways to build, optimize, and automate ML pipelines, with a specialization in Google Cloud Platform and TensorFlow. During this journey, she has also had the opportunity to experience many aspects of a business outside of technical, from line management and recruiting to marketing, thought leadership, and pre-sales.
Linux, MacOS, Google Cloud Platform (GCP), XGBoost, Scikit-learn, Keras, Python, Docker, Amazon Web Services (AWS), Kubernetes
The most amazing...
...project I've led was a computer vision model that identified products from in-app images; >95% accuracy, 60% package-free product, and lots of plastic saved!
Technical Writer | Consultant
IOD Cloud Technologies Research Ltd.
- Wrote over 30 articles as a ghostwriter and thought-leadership pieces for various data science, data, and AI companies.
- Increased the online engagement on the website for client companies by around three times.
- Performed in-depth research into topics ranging from TF Serving to ML model governance and data fabric.
- Developed a system requirement design document outlining the business use case, architecture design, and functional requirements of lift&shifting the current infrastructure to Kubeflow.
- Consulted on the implementation plan for the lift&shift of the infrastructure, with a PoC delivered by the team in two-weeks time.
- Consulted on the pros and cons of different solutions to Kubeflow, focusing on Vertex AI and other cloud solutions.
Machine Learning Engineer
- Ideated, designed, and delivered the automated retraining pipeline for the fraud engine model.
- Ideated, 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.
Senior Machine Learning Engineer
- Led and delivered multiple consulting projects in data science, AI optimization and automation from the qualification call to client engagement and project delivery with and NPS of 100.
- Conceptualized the AI automation practice together with the chief data scientist from offerings to client profiles and deliverables, with the creation and delivery of strategic and marketing material to the internal team, clients, and stakeholders.
- Drove the technical partnership with Intel through multiple R&D projects resulting in thought leadership pieces with thousands of views on our website and presented at multiple conferences.
- Line managed and mentored juniors to improve their technical and personal skills, define and achieve their OKRs, and become more proactive towards what they enjoy and want to learn.
- Initiated and coordinated multiple internal initiatives for the team including all hands days, Niko-Niko calendar, surveys, and OKR sessions.
- Published and oversaw several articles on the company’s blog, from technical topics to event communications in the AI scene.
- Provided training to global market leaders on the best practices for machine learning on GCP.
Machine Learning Researcher
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.
Machine Learning Intern
- 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.
ML Pipeline Automation with Kubeflow
Marketing Analytics - Brand Propensity Scoring
Object Detection for News Articles Retrieval
Python, SQL, Snowflake
TensorFlow, Pandas, XGBoost, Scikit-learn, Keras, Google Cloud Video API, Google Cloud API, Dask, PyTorch
Jupyter, Amazon SageMaker, 2Checkout, Cloud Dataflow, Google Kubernetes Engine (GKE), BigQuery, TeamCity, Jenkins, Google Cloud AI, Azure Machine Learning
Data Science, Database Design, Management, Automation, Agile Software Development, DevOps
Google Cloud Platform (GCP), Linux, Docker, MacOS, RapidMiner, Kubernetes, Amazon Web Services (AWS)
Kubeflow, Machine Learning, Computer Vision, Consulting, Thought Leadership, Artificial Intelligence (AI), Recommendation Systems, Algorithms, Deep Neural Networks, Neural Networks, Presales, Sentiment Analysis, Machine Learning Automation, Google Cloud Machine Learning, Object Detection, Deep Learning, Content Writing, Image Processing, Big Data, Technical Writing, Convolutional Neural Networks, OCR, Image Recognition, Writing & Editing, Blogging, 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)
Master's Degree in AI & Robotics
Sapienza - Rome, Italy
Bachelor's Degree in Information Technology
RomaTre - Rome, Italy
Machine Learning Engineering for Production (MLOps)
DeepLearning.AI | via Coursera
Google Cloud Certified Professional Machine Learning Engineer
Google Cloud Certified Cloud Architect
Google Cloud Certified Data Engineer
Cambridge English: Proficiency (CPE)
University of Cambridge
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