Alan is available for hire
Hire AlanAlan Sammarone
Verified Expert in Engineering
AI and ML Developer
Amsterdam, Netherlands
Toptal member since March 28, 2017
Bio
Alan is an innovative software, research, and machine learning (ML) engineer with over a decade of experience idealizing, researching, building, and deploying machine learning applications. He excels in fast-paced startup environments and drives cutting-edge AI/ML solutions from concept to deployment.
Portfolio
Enza Zaden
Python, Azure, PyTorch, JAX, Computer Vision, Spectroscopy, Terraform, Linux...
Nav
Python, Kubernetes, JAX, PyTorch, Apache Kafka, Linux, Machine Learning...
Tillful
Python, PyTorch, Kubernetes, Machine Learning, PostgreSQL, Apache Kafka, Linux...
Experience
- Python - 12 years
- Linux - 10 years
- PostgreSQL - 10 years
- Machine Learning - 6 years
- PyTorch - 5 years
- Kubernetes - 4 years
- Apache Kafka - 3 years
- Terraform - 2 years
Preferred Environment
Python
The most amazing...
...thing I've built and deployed was an ML system combining several cutting-edge techniques, such as weak supervision and latent space anchoring.
Work Experience
Lead AI Engineer, Tech Lead and Architect
2024 - PRESENT
Enza Zaden
- Built a team of ML engineers and data scientists aimed at being the core group responsible for guiding the company through a data-driven transformation phase.
- Collaborated with the data science, biology, bioinformatics, and robotics teams to improve the ML solution lifecycle management.
- Worked with business stakeholders to define the company's machine learning strategy for the next 3-5 years and build the core infrastructure and tooling used by multiple R&D and operations teams within the company.
Technologies: Python, Azure, PyTorch, JAX, Computer Vision, Spectroscopy, Terraform, Linux, Machine Learning, Git, Mathematical Analysis, Neural Networks, NumPy, Docker, FastAPI, Streamlit, Python 3, Large Language Models (LLMs), OpenAI, Technical Leadership, Software Architecture, Web Development, AI Agents, Azure Blob Storage, Artificial Intelligence (AI), Cloud Architecture, Biology, Retrieval-augmented Generation (RAG), LangChain, Machine Learning Operations (MLOps), Genomics, Real-time Systems, Statistical Modeling, Google Cloud Platform (GCP), CI/CD Pipelines, Helm, DevOps, Grafana, Cloud Monitoring, Test-driven Development (TDD), SciPy, Pytest, AI Automation, LLM Integration, AI Engineering, MLflow, Back-end, Claude Code, Claude, REST APIs, Agentic AI, GitHub, Infrastructure as Code (IaC)
Principal AI + Full Stack Engineer
2023 - 2024
Nav
- Designed and led a team implementing the company-wide software infrastructure aimed at serving various machine learning models at scale with real-time inferences using an event-based architecture with Kafka.
- Collaborated with technical and product stakeholders to create and implement a migration from nightly batch jobs to real-time processing with Kafka. This ultimately led to features being available to end users much faster and reduced customer churn.
- Migrated the acquisition IP to the company's infrastructure.
Technologies: Python, Kubernetes, JAX, PyTorch, Apache Kafka, Linux, Machine Learning, Amazon Web Services (AWS), Git, Neural Networks, PostgreSQL, NumPy, Docker, APIs, Algorithms, Data Science, FastAPI, Flask, SQLAlchemy, SQL, Python 3, Large Language Models (LLMs), Data Visualization, Data Analysis, Technical Leadership, Software Architecture, Web Development, Artificial Intelligence (AI), Distributed Systems, Redis, Event-driven Design (EDD), Cloud Architecture, Google Cloud, Retrieval-augmented Generation (RAG), Machine Learning Operations (MLOps), Real-time Systems, Statistical Modeling, CI/CD Pipelines, Helm, DevOps, Grafana, Cloud Monitoring, Test-driven Development (TDD), SciPy, Pytest, GitLab CI/CD, Cloud Run, AI Engineering, MLflow, AI Model Training, Back-end, GitHub, Infrastructure as Code (IaC)
Senior ML Full-stack Engineer
2018 - 2023
Tillful
- Transformed a proof-of-concept into a fully functional, production-ready financial transaction categorization engine, employing natural language processing, time series analysis, and weak supervision techniques.
- Designed and implemented the production-ready machine learning pipeline for a pre-incident model used by one of Europe's largest banks. The pipeline processes 10 TB per run and uses Spark, Kubeflow Pipelines, XGBoost, and Kubernetes.
- Collaborated closely with research scientists, software engineers, architects, and stakeholders to design and implement multiple machine learning solutions aimed at serving machine learning models at scale to Fortune 500 companies.
Technologies: Python, PyTorch, Kubernetes, Machine Learning, PostgreSQL, Apache Kafka, Linux, Amazon Web Services (AWS), Git, Mathematical Analysis, Neural Networks, NumPy, Docker, Trading Systems, Trading, APIs, Algorithms, Data Science, Flask, SQLAlchemy, Pandas, SQL, Twilio, Python 3, Large Language Models (LLMs), Data Visualization, Data Analysis, Software Architecture, Web Development, Celery, RabbitMQ, Distributed Systems, Event-driven Design (EDD), Cloud Architecture, Machine Learning Operations (MLOps), Real-time Systems, CI/CD Pipelines, DevOps, Grafana, Cloud Monitoring, Test-driven Development (TDD), SciPy, Pytest, GitLab CI/CD, AI Model Training, Back-end, GitHub, Infrastructure as Code (IaC)
Senior Developer
2014 - 2017
Simbiose Ventures
- Created a machine-learning pipeline as well as a REST API to access it, which was able to categorize websites according to their contents.
- Optimized various parts of the company's system, generating a 5 to 10-fold performance improvement and decreased costs.
- Migrated the company's storage architecture to a hybrid of Amazon Glacier and Amazon S3, decreasing storage costs by 30%.
- Idealized and oversaw the creation of a system for extracting product prices for any given URL representing a product listing.
Technologies: Amazon Web Services (AWS), Amazon, C, Aerospike, Elasticsearch, Python, Linux, Git, Mathematical Analysis, PostgreSQL, JavaScript, APIs, MySQL, Data Scraping, Algorithms, Web Scraping, SQLAlchemy, Pandas, API Integration, Django, SQL, React, Python 3, Cython, Web Development, Distributed Systems, Real-time Systems, Test-driven Development (TDD), Pytest, Back-end, GitHub
Software Developer
2012 - 2014
Positivo Informática
- Coded highly optimized, browser-based mathematical and physical simulations aimed at helping teaching high school children visualize concepts.
- Wrote an automation tool used to update and deploy thousands of applications efficiently.
- Optimized many legacy JavaScript projects to make them run on low-end tablets.
Technologies: Python, Git, Linux, JavaScript, MySQL, SQL, Python 3, Web Development
Junior Developer
2010 - 2012
Aymará Editora
- Coded and supported a social network aimed at children.
- Wrote JavaScript animations and games for tablets.
- Created a framework to sync information from different databases.
Technologies: PHP, Git, Linux, SQL
Junior Developer
2009 - 2010
Totalize Internet Studio
- Created websites for small and medium-sized businesses using a proprietary framework.
- Customized administrative tools and worked closely with engineers focused on securing the platform.
- Communicated with clients to gather requirements and triage bug reports.
Technologies: PHP, Git, Linux
Experience
Scalable and Weakly Supervised Bank Transaction Classification
https://arxiv.org/abs/2305.18430We developed an end-to-end system for bank transaction classification using weak supervision and deep learning.
I was involved in the ideation and research phases and led the productionization effort. My work included designing and implementing the real-time inference architecture, integrating the system with Kafka and KSQL for event batching, and deploying scalable models via Kubernetes and Kubeflow Pipelines.
The system uses heuristics and unsupervised embeddings to generate weak labels, which are then used to train GRU-based discriminative models. Our pipeline outperformed Plaid API in several tasks, achieving over 90% accuracy across nine financial categories. The architecture was optimized for rapidly onboarding new classification tasks with minimal manual effort.
I was involved in the ideation and research phases and led the productionization effort. My work included designing and implementing the real-time inference architecture, integrating the system with Kafka and KSQL for event batching, and deploying scalable models via Kubernetes and Kubeflow Pipelines.
The system uses heuristics and unsupervised embeddings to generate weak labels, which are then used to train GRU-based discriminative models. Our pipeline outperformed Plaid API in several tasks, achieving over 90% accuracy across nine financial categories. The architecture was optimized for rapidly onboarding new classification tasks with minimal manual effort.
Voice-controlled Customer Service Agent
The project is a Python back end for an MVP that delivers an interactive voice interface capable of handling end-to-end customer support tasks without human intervention. It leverages three OpenAI capabilities in sequence: gpt-4o-transcribe to convert speech to text, gpt-4o (with tool-calling support) to process the input and generate a response, and gpt-4o-mini-tts to convert the response back to speech.
Vulkan, AI Image and Video Generation Platform
Built and operate Vulkan, an AI image and video generation platform, entirely solo (bootstrapped, alongside full-time role), FastAPI and Postgres back end with NATS-based job dispatch to distributed GPU workers (Flux2, WAN video, ComfyUI pipelines), provisioned on spot GPU instances by a custom control plane, media served through a Cloudflare edge gateway with signed URLs backed by R2; Stripe payments, centralized observability with OpenObserve, single-command declarative deploys, wrote the threat model and security review gating public launch.
Education
2022 - 2024
Master's Degree in Theoretical Physics
University of Amsterdam - Amsterdam
2020 - 2022
Master's Degree in Computational Science
University of Amsterdam - Amsterdam
2016 - 2019
Bachelor's Degree in Physics
Universität Leipzig - Leipzig, Germany
Skills
Libraries/APIs
NumPy, SciPy, SQLAlchemy, Pandas, Flask API, REST APIs, PyTorch, JAX, React, ArcGIS
Tools
Pytest, Claude Code, Claude, GitHub, Terraform, Apache Airflow, Celery, RabbitMQ, Helm, Grafana, GitLab CI/CD, Git
Languages
Python, SQL, Python 3, JavaScript, PHP, C
Frameworks
Flask, Django, Streamlit
Paradigms
Real-time Systems, DevOps, Test-driven Development (TDD), Event-driven Design (EDD)
Storage
PostgreSQL, MySQL, Redis, Elasticsearch, Aerospike, Google Cloud
Platforms
Amazon Web Services (AWS), Kubernetes, Apache Kafka, Docker, Raspberry Pi, Twilio, Google Cloud Platform (GCP), Cloud Run, Amazon, Linux, Azure
Industry Expertise
Trading Systems
Other
Machine Learning, APIs, Large Language Models (LLMs), Web Development, Artificial Intelligence (AI), Machine Learning Operations (MLOps), CI/CD Pipelines, AI Engineering, AI Model Training, Back-end, Agentic AI, Infrastructure as Code (IaC), Data Scraping, Algorithms, Web Scraping, Data Science, FastAPI, API Integration, Cython, OpenAI, Data Visualization, Data Analysis, Technical Leadership, Software Architecture, AI Agents, Azure Blob Storage, Distributed Systems, Cloud Architecture, Retrieval-augmented Generation (RAG), LangChain, Prompt Engineering, Statistical Modeling, Voice AI, DSP, Cloud Monitoring, AI Automation, LLM Integration, MLflow, Mathematical Analysis, Apache Cassandra, Neural Networks, Physics, Computer Vision, Spectroscopy, Chrome Extensions, Trading, Leadership, Ideation, Delivery, Biology, Genomics, Containers
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