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Florijan Stamenković
Verified Expert in Engineering
Machine Learning Developer
Zagreb, Croatia
Toptal member since August 1, 2018
Bio
Since 2004, Florijan has worked on a wide range of projects such as machine-learning platforms for large Croatian and Austrian sites, a high-performance database engine in C++, client-server systems in Java and more. Besides having strong technical skills, Florijan excels at translating a client's ideas and needs into fully functional software and has experience in project management and leading teams.
Portfolio
Linde
Large Language Models (LLMs), OpenAI API, Prompt Engineering...
ABC-Plan, Inc
Algorithms, Test-driven Development (TDD), Python, Machine Learning...
Undisclosed
Computer Vision, Python, Amazon Web Services (AWS), NumPy, OpenCV, AWS Lambda...
Experience
- Python - 15 years
- Machine Learning - 15 years
- Databases - 12 years
- Large Language Models (LLMs) - 10 years
- Artificial Intelligence (AI) - 10 years
- Cloud Infrastructure - 10 years
- Computer Vision - 8 years
- Amazon Web Services (AWS) - 8 years
Preferred Environment
C++, Python, Data Science, Machine Learning
The most amazing...
...project I've led and implemented was a real-time, personalized recommendation system for the largest Croatian media company.
Work Experience
Machine Learning Engineer
2025 - 2025
Linde
- Contributed to document processing and automation system using OCR and LLM technologies. Implemented data extraction and structuring pipelines.
- Contributed to a RAG pipeline (embeddings, search, retrieval, generation) and LLM-based agentic systems.
- Researched LLM-based complex information processing automation. Implemented and tested prototypes.
- Worked on general infrastructure and code quality, covering testing, custom package management, CI pipelining, git, Azure, async Python, queues, etc.
Technologies: Large Language Models (LLMs), OpenAI API, Prompt Engineering, Retrieval-augmented Generation (RAG), Python, Azure, Visual Language Models (VLMs), Azure AI Document Intelligence, Optical Character Recognition (OCR), Artificial Intelligence (AI), Docker, Agentic AI, Git, SQL, Embeddings from Language Models (ELMo), Test-driven Development (TDD), Asyncio, Cloud Infrastructure, Databases, Matplotlib, LangChain, Generative Artificial Intelligence (GenAI), OAuth, Communication, AI Agents, AI Pipeline, Vector Databases, Architecture, Solution Architecture, Model Deployment, Chatbots, AI Tools, OpenAI, Claude, n8n, Deployment, Open-source LLMs, Workflow Automation, Back-end Architecture, Document Parsing, Vector Search
Algorithm Expert
2024 - 2024
ABC-Plan, Inc
- Improved pharmaceutical production pipeline planning.
- Implemented and optimized a complex scheduling algorithm.
- Improved the software definition based on existing implementation and tests.
Technologies: Algorithms, Test-driven Development (TDD), Python, Machine Learning, Google Cloud Platform (GCP), Pytest, NumPy, SciPy, OpenAI
Computer Vision Expert
2024 - 2024
Undisclosed
- Conceived and implemented a computer vision pipeline for the processing of macro photography previously done by human experts.
- Tuned multiple processing algorithms based on the client's proprietary dataset and optimized algorithm performance.
- Deployed computer vision processing APIs on AWS, utilizing Lambda, S3, and EC2.
- Supported the development of a front-end application for using the developed pipelines.
Technologies: Computer Vision, Python, Amazon Web Services (AWS), NumPy, OpenCV, AWS Lambda, Cloud Infrastructure, GitHub, Matplotlib, Object Recognition, Image Manipulation, Rendering, Communication, Architecture, Solution Architecture, Deployment, Workflow Automation, Back-end Architecture, Image Segmentation
MLOps Engineer via Toptal
2023 - 2024
Brain Craft Limited
- Designed and implemented an ML job execution platform based on a set of custom-developed services, AWS, and cloud GPU providers.
- Utilized Docker and Docker Compose for the development and production deployment of multiservice stacks to support ML model usage.
- Integrated multiple GPU cloud provider platforms (notably Vast.ai and RunPod) into a self-monitored, automated system.
- Prepared several models for production deployment (text-to-video generation, object detection, and image inpainting).
- Optimized the performance of image processing services through image preprocessing and model tuning.
- Coordinated two junior team members who were developing support for other ML models based on the same stack.
Technologies: Artificial Intelligence (AI), Machine Learning Operations (MLOps), Graphics Processing Unit (GPU), Machine Learning, Docker, Docker Hub, Docker Compose, PyTorch, Python, uWSGI, Flask, Amazon Web Services (AWS), OpenCV, PIL, APIs, Unit Testing, Pytest, pylint, DevOps, Data Pipelines, SQL, Infrastructure, Application Performance Monitoring, Multithreading, Algorithms, Test-driven Development (TDD), Cloud Infrastructure, GitHub, Object Recognition, Image Manipulation, TensorFlow, AI Pipeline, Architecture, Solution Architecture, AI Agents, Model Deployment, AI Tools, OpenAI, Deployment, Local Hosting, Workflow Automation, Back-end Architecture
Data Scientist (via Toptal)
2023 - 2023
Roompulse A.E.
- Developed and optimized price estimation and anomaly detection algorithms in the hospitality domain.
- Used OpenAI GPT models for text analysis, processing, and inference.
- Contributed to and advised on data gathering and cloud pipeline approaches.
Technologies: Data Science, Machine Learning, Revenue Optimization, Pricing Strategy, Databases, Natural Language Processing (NLP), OpenAI GPT-4 API, Large Language Models (LLMs), ChatGPT, pylint, Data Pipelines, SQL, Machine Learning Operations (MLOps), Python, Docker, Amazon Web Services (AWS), OpenAI API, Prompt Engineering, Cloud Infrastructure, GitHub, Clustering, OpenAI, Deployment, Open-source LLMs, Workflow Automation
Cloud Architecture Engineer
2022 - 2023
Pangea Botanica (via Scalexa)
- Designed, developed, and deployed a job execution platform on AWS supporting massive parallel execution, GPU execution, on-demand scaling, map-reduce, queuing, etc.
- Developed and integrated data acquisition, processing, and versioning pipelines for multiple public chemical databases.
- Implemented APIs and CLI tools for platform interactions (job execution and data acquisition).
Technologies: Python, Amazon Web Services (AWS), Amazon Elastic Container Service (ECS), Docker, Flask, Bash Script, DevOps, Unit Testing, Pytest, pylint, AWS Fargate, Data Pipelines, SQL, Infrastructure, Application Performance Monitoring, Machine Learning Operations (MLOps), Multithreading, Test-driven Development (TDD), REST, Embeddings from Language Models (ELMo), Cloud Infrastructure, Databases, GitHub, Generative Artificial Intelligence (GenAI), OAuth, Communication, Linux, AI Pipeline, Vector Databases, Architecture, Solution Architecture, Model Deployment, AI Tools, Deployment, Workflow Automation, Back-end Architecture
Computer Vision Developer
2022 - 2023
Inci Islim
- Used OpenCV to detect augmented-reality markers in the video.
- Implemented algorithms for improved marker tracking resilience.
- Implemented visualizations and annotations over existing videos.
Technologies: Python, OpenCV, Scripting, Video Processing, Statistics, pylint, Multithreading, GitHub, Image Manipulation
Machine Learning Engineer
2022 - 2022
Kesef Global Pty Ltd
- Optimized Large Language Models (LLMs) on a specialized dataset using state-of-the-art models and tech (Hugging Face models, Accelerate, DeepSpeed).
- Worked on model reduction (quantization, pruning) and training speed optimizations.
- Analyzed the Bittensor platform codebase (nodes, datasets) and suggested development directions based on findings.
Technologies: Machine Learning, Causal Inference, PyTorch, Language Models, Data Inference, Fine-tuning, DeepSpeed, Python, Text Generation, Large Language Models (LLMs), ChatGPT, pylint, Embeddings from Language Models (ELMo), GitHub, AI Pipeline, Model Deployment, AI Tools, Open-source LLMs
Data Scientist | Machine Learning Engineer
2022 - 2022
Procureship S.A.
- Developed a recommendation engine based on previous procurement data.
- Wrapped the recommendation engine into an easily deployable web service.
- Educated the client about the recommendation-engine fundamentals, data requirements, and basic algorithms and advised on future development.
Technologies: Data Science, Machine Learning, Recommendation Systems, Algorithms, Python, Scikit-learn, Flask, Docker, Unit Testing, pylint, DevOps, Data Pipelines, Cloud Infrastructure, GitHub, Clustering, SQL, Model Deployment, Deployment
Machine Learning Engineer
2022 - 2022
Microblink
- Researched current state-of-the-art recommendation systems for eCommerce and worked on several implementations of such systems.
- Analyzed purchase data, testing various premises supporting buyer behavior predictions.
- Used TensorFlow and Docker to develop encapsulated machine learning services.
Technologies: Recommendation Systems, Machine Learning, Python, TensorFlow, Data Science, Artificial Intelligence (AI), Image Processing, Data Visualization, SQL, Docker, Machine Learning Operations (MLOps), Data, User Behavior, Keras, Analytics, PostgreSQL, Data Engineering, Git, Cloud, Neural Networks, Predictive Modeling, Python 3, Back-end, Multithreading, Embeddings from Language Models (ELMo), Databases, Clustering, Matplotlib, Communication, AI Pipeline, AI Tools, Vector Search
Computer Vision Researcher | Engineer
2021 - 2022
Photomath
- Proposed and developed multiple prototype systems in computer vision.
- Researched existing state-of-the-art computer vision papers and implemented some of them.
- Developed and deployed neural network-based computer vision tools and classic computer vision (OpenCV) algorithms.
Technologies: Machine Learning, Computer Vision, Python, PyTorch, OpenCV, Data Science, Computer Graphics, Artificial Intelligence (AI), Image Processing, Data Visualization, Docker, Machine Learning Operations (MLOps), Data, Technology Consulting, Object Detection, Computer Vision Algorithms, Microservices, Data Extraction, Git, Jupyter, Cloud, Neural Networks, Predictive Modeling, Python 3, Back-end, Pytest, pylint, Multithreading, Amazon Web Services (AWS), Matplotlib, Object Recognition, Image Manipulation, Communication, AI Tools, Document Parsing, Image Segmentation
Machine Learning Engineer
2020 - 2021
Velebit AI
- Evaluated papers on portrait segmentation and chose them among competitive approaches regarding available data and requirements.
- Worked on network architecture and model training. Implemented data processing pipelines (preprocessing, augmentation, and visualization). Prepared tooling for data labeling.
- Evaluated papers on object detection and adapted algorithms to a specific domain.
Technologies: Deep Learning, Machine Learning, Computer Vision, PyTorch, Python, Scikit-image, OpenCV, Data Science, Computer Graphics, Artificial Intelligence (AI), Image Processing, Data Visualization, Docker, Machine Learning Operations (MLOps), Data, Technology Consulting, Object Detection, Computer Vision Algorithms, Object Tracking, MySQL, Git, Jupyter, Cloud, Data Analytics, Neural Networks, Predictive Modeling, Python 3, Unit Testing, Pytest, pylint, Test-driven Development (TDD), Amazon Web Services (AWS), Large Language Models (LLMs), REST, Databases, GitHub, Object Recognition, Image Manipulation, Rendering, LangChain, SQL, Generative Artificial Intelligence (GenAI), Communication, TensorFlow, AI Pipeline, Vector Databases, Model Deployment, AI Tools, Deployment, Vector Search, Image Segmentation
Python Developer | Data Engineer
2019 - 2021
Labelbox
- Designed and implemented the Labelbox Python SDK, open-sourced at Github.com/Labelbox/labelbox-python, and available on PyPI (pip install labelbox).
- Worked on ETL pipelines using the Google Cloud Platform (BigQuery and Data Studio) for analytics.
- Worked on massive parallel processing using Apache Beam (GCP Dataflow) for image processing.
- Used Apache Airflow (GCP Cloud Composer) for job scheduling (ETL and periodic recalculations).
- Worked on IAM integrations and automation for GCP and AWS.
- Implemented queue-based (RabbitMQ and Celery) data processing pipelines.
Technologies: Data Analysis, Algorithms, Pika, AMQP, GraphQL, Google Data Studio, AWS IAM, Google Cloud Platform (GCP), Storage, BigQuery, Apache Beam, Apache Airflow, Python, RabbitMQ, Celery, Data Science, Machine Learning, Computer Graphics, Artificial Intelligence (AI), SQL, Redis, Docker, Machine Learning Operations (MLOps), Data, GIS, Big Data, REST APIs, Analytics, Object Tracking, Serverless, Microservices, Data Engineering, ETL, Git, API Integration, API Documentation, Cloud, Open Source, Data Analytics, Python 3, CI/CD Pipelines, Back-end, Unit Testing, Pytest, pylint, Google Cloud, DevOps, Data Pipelines, Kubernetes, Infrastructure, Application Performance Monitoring, Multithreading, Test-driven Development (TDD), Amazon Web Services (AWS), Embeddings from Language Models (ELMo), Cloud Infrastructure, Databases, GitHub, OAuth, Communication, AI Pipeline, Architecture, Solution Architecture, AI Tools, Deployment, Back-end Architecture
NLP Engineer
2020 - 2020
QiO
- Implemented a semantic search engine tailored for a specific domain (database of documents).
- Implemented an event extraction (from natural language), supporting a platform for converting unstructured to structured data.
- Applied topic modeling and text summarization algorithms.
Technologies: Python, SpaCy, Optical Character Recognition (OCR), NumPy, Scikit-learn, Data Science, Machine Learning, Artificial Intelligence (AI), Data, Data Analysis, Large Language Models (LLMs), Technology Consulting, Search Engines, Serverless, Data Extraction, Git, Data Analytics, Neural Networks, Predictive Modeling, Python 3, Language Models, GitHub
Data Science Consultant
2020 - 2020
Picks and Pickers S.L.
- Evaluated the current state of the social network in Picks and Pickers and recommended an approach for improving engagement.
- Evaluated client and product data regarding the possibilities of making a product recommendation engine.
- Analyzed the product database for possibilities of deduplication and product description similarity matching and merging.
- Implemented a text classifier using Scikit-learn and Flask.
Technologies: Data Analysis, Machine Learning, Recommendation Systems, NetworkX, Pandas, Data Science, Python, Artificial Intelligence (AI), Data, Technology Consulting, Serverless, Git, Data Analytics, Predictive Modeling, Python 3, Data Pipelines, GitHub, Clustering
Machine Learning Consultant
2019 - 2019
Sensie
- Supported a wellness application for stress detection based on mobile device sensor data.
- Implemented and evaluated machine learning classifiers based on motion sensor data.
- Deployed machine learning models using Google Cloud Function.
- Analyzed existing classification algorithms and advised on the future development.
Technologies: Deep Learning, Machine Learning, Google Cloud, Scikit-learn, Python, Data Science, Artificial Intelligence (AI), Technology Consulting, Serverless, Microservices, AWS Lambda, Git, Data Analytics, Neural Networks, Predictive Modeling, Python 3, GitHub, Model Deployment
Information Retrieval Engineer | Analyst
2018 - 2019
Piggy | Joinpiggy.com
- Implemented custom information retrieval (search) algorithms based on NLP and ML using Sklearn and Numpy.
- Implemented a custom database search algorithm based on textual query ranking and geographical closeness, using Sklearn and Scipy.
- Optimized service for low latency and high throughput workloads using Numpy and Cython. Prepared the deployment using Flask.
- Provided analytics of user behavior data in numeric and visual form using DynamoDB, Pandas, and Matplotlib.
- Implemented data-reduction, aggregation, and anonymization pipelines for delivery to third parties.
Technologies: Data Analysis, Algorithms, Machine Learning, Scikit-learn, Cython, SciPy, NumPy, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Python, Data Science, Redis, Data Visualization, Data, GIS, Technology Consulting, Search Engines, MySQL, Microservices, AWS Lambda, Git, Data Analytics, Predictive Modeling, Statistics, Python 3, Back-end, Unit Testing, Pytest, Google Cloud, Data Pipelines, SQL, Infrastructure, Amazon Web Services (AWS), Large Language Models (LLMs), REST, Embeddings from Language Models (ELMo), Databases, Workflow Automation
Data Scientist for Cost Regression
2018 - 2018
ARTA Shipping, Inc.
- Implemented a regression model for a fine-art shipping cost estimation using Pandas and Sklearn.
- Performed data analysis using Pandas. Generated reports and visualization of the data using Matplotlib.
- Implemented a prediction service utilizing the optimized model using Flask.
- Implemented a training, reporting, and deployment pipeline for continuous integration.
Technologies: Data Analysis, Machine Learning, Flask, Matplotlib, GeoNames, SQL, Scikit-learn, Pandas, Python, Data Science, Data Visualization, Geospatial Data, GIS, Analytics, Technology Consulting, Git, Predictive Modeling, Python 3, Unit Testing, Pytest, Docker, Cloud Infrastructure, GitHub, Clustering, Deployment, Back-end Architecture
Software Engineer on a Transactional Database Engine
2017 - 2018
Memgraph
- Worked on a transactional, distributed, in-memory graph database engine focused on high-performance using modern C++ (14 and 17 standards).
- Worked on a query compiler, including parsing, syntactic and semantic analysis, intermediary codes, interpretation, and compilation.
- Built a distributed database engine version with dynamic sharding and balancing capabilities.
- Worked on a multi-version concurrency control (MVCC) based transaction engine for a parallel query execution with snapshot guarantees.
- Worked on concurrent data structures and algorithms.
- Developed in a very-high standard environment: continuous integration, in-depth code reviews, unit/integration/compliance testing, and performance regression analysis.
Technologies: Algorithms, Bash, Python, Google Test, ANTLR, Standard Template Library (STL), C++17, C++14, Docker, Data, Search Engines, PostgreSQL, Data Modeling, Data Engineering, Git, CI/CD Pipelines, Back-end, Unit Testing, Abstract Syntax Trees (AST), Data Pipelines, Multithreading, Test-driven Development (TDD), Amazon Web Services (AWS), Databases, SQL, Communication, Linux, Vector Databases, Architecture, Solution Architecture, Local Hosting
Technical Lead
2015 - 2017
Styria Data Science
- Acted as the technical data science lead during the growth of a newly founded machine learning department from three to more than ten employees.
- Prototyped, developed, and deployed machine-learning software for some of the largest Croatian (24sata.hr and Njuskalo.hr) and Austrian (Willhaben.at) sites.
- Built NLP models for real-time, personalized recommendations with a microservice stack around it. Used neural networks, autoencoder stacks, word and paragraph embeddings, and more.
- Developed computer vision technology for image classification, similarity, and object detection, using traditional computer vision methods and neural networks (deep learning).
- Handled GPU deployments, both locally and on AWS. Worked on S3 data pipelines, data processing automation, model, and runtime speed optimizations.
- Acted as the technical evaluator in the hiring process for developers and interns.
Technologies: Amazon Web Services (AWS), Data Analysis, Deep Learning, Machine Learning, Boto, Amazon EC2, Amazon S3 (AWS S3), PIL, Flask, SciPy, NumPy, Theano, TensorFlow, Python, Data Science, Computer Graphics, Artificial Intelligence (AI), Image Processing, Computer Vision, Data Visualization, SQL, Redis, Docker, Machine Learning Operations (MLOps), Data, User Behavior, Product Leadership, Big Data, REST APIs, Keras, Analytics, Large Language Models (LLMs), Technology Consulting, Object Detection, Computer Vision Algorithms, Search Engines, PostgreSQL, MySQL, Data Modeling, Microservices, AWS Lambda, Data Engineering, ETL, Project Management, Git, Jupyter, API Integration, Cloud, Data Analytics, Neural Networks, Predictive Modeling, Statistics, Python 3, CI/CD Pipelines, Back-end, Language Models, Unit Testing, Pytest, DevOps, Data Pipelines, Infrastructure, Application Performance Monitoring, Multithreading, Algorithms, Test-driven Development (TDD), REST, Recommendation Systems, Embeddings from Language Models (ELMo), Cloud Infrastructure, Databases, GitHub, Clustering, Matplotlib, OpenCV, Object Recognition, Image Manipulation, Rendering, Generative Artificial Intelligence (GenAI), OAuth, Communication, Linux, AI Pipeline, Vector Databases, Architecture, Solution Architecture, Model Deployment, AI Tools, Deployment, Local Hosting, Open-source LLMs, Back-end Architecture, Document Parsing, Vector Search, Image Segmentation
Software Engineer
2004 - 2009
CNG Havaso Ltd.
- Worked as the lead programmer in a small startup, focusing on production-site data management.
- Developed a modular client-server system for issue-tracking, inventory, and bookkeeping.
- Implemented the back end using Java, Apple's WebObjects, and Enterprise Objects frameworks, backed by Openbase and Frontbase.
- Implemented a desktop application connecting to the Web Objects app server using Java Swing.
- Developed and open-sourced JBND, a Swing data-binding library for rapid application development.
- Gave a talk at the worldwide WebObjects conference in San Francisco (2008) on JBND and desktop client apps.
Technologies: Algorithms, Enterprise Objects Framework (EOF), Web, SQL, Java, WebObjects, Object-oriented Programming (OOP), Data, Product Leadership, Technology Consulting, PostgreSQL, MySQL, Data Modeling, Data Engineering, Project Management, API Documentation, Open Source, Back-end, Unit Testing, Data Pipelines, Infrastructure, Multithreading, Test-driven Development (TDD), Databases, Communication, Architecture, Solution Architecture, Deployment, Back-end Architecture
Experience
Memgraph
https://memgraph.com/In Memgraph, I worked as a core engineer on a modern transactional graph database. I was involved with system design, database state, partitioning, parallelism, data structures, etc. As part of a small team of core engineers, I worked on most aspects of the database.
Labelbox Python SDK
https://github.com/Labelbox/labelbox-pythonThe Python SDK for the Labelbox platform. The SDK is a client-side stub for interacting with Labelbox GraphQL back-end. It provides Python objects (ORM) transparent client-server interaction, pagination, and more.
Willhaben Fashion Camera
The fashion cam is a machine-learning-based system where users search for similar clothes based on existing classified ads or their own photos. The system has been expanded to other domains such as antique furniture and further enhancements are planned.
I worked as the tech lead of the development team, overseeing the model implementation and evaluation, data pipelining (large volumes of images transferred between Austrian hosting, AWS Ireland, Germany, and Croatian hosting), search-engine runtime implementation, and product development.
I worked as the tech lead of the development team, overseeing the model implementation and evaluation, data pipelining (large volumes of images transferred between Austrian hosting, AWS Ireland, Germany, and Croatian hosting), search-engine runtime implementation, and product development.
Object Detection in 3D
https://www.youtube.com/watch?v=v5ubMhAki_QI collaborated with my friends and colleagues from Velebit AI on a POC for detecting objects in 3D based on 2D photographs projected into a 3D point cloud. The system will be used in real estate or site management but likely offers many other possibilities. We used OpenGL to develop a visualization system to better inspect, understand and improve model behavior.
Personalized Recommendater for 24sata.hr
https://www.24sata.hr/On this project, I led the design, implementation, and deployment of a personalized content recommendation system for the largest Croatian tabloid organization, among other things. It was a real-time multiple-website system intended to also support direct monetization through advertisements.
Regression Modeling for ShipArta
https://shiparta.com/I analyzed and processed data as well as provided regression modeling for ShipArta, one of the world's leading global shipping services, which specializes in the safe transportation of fine art pieces.
Sensie Stress Detection
I provided consulting for a wellness startup that aims to detect stress based on mobile device motion sensors. I helped the Sensie team start the migration from a custom-feature classification system toward a more streamlined machine-learning-based approach. Also advised and helped them with deploying machine learning algorithms on Google Cloud.
Education
2013 - 2015
Master's Degree in Computer Science
University in Zagreb - Zagreb, Croatia
2010 - 2013
Bachelor's Degree in Computer Science
University in Zagreb - Zagreb, Croatia
Certifications
JANUARY 2016 - PRESENT
Sun Certified Java Programmer
Oracle
Skills
Libraries/APIs
Pandas, TensorFlow, Scikit-learn, PIL, PyTorch, NumPy, OpenCV, SQLAlchemy, Theano, REST APIs, Keras, OpenAI API, Asyncio, AMQP, Google API, Google APIs, NetworkX, Pika, SciPy, Matplotlib, Standard Template Library (STL), SpaCy, Protobuf, OpenGL, DeepSpeed
Tools
Pytest, GitHub, Git, TensorBoard, Phabricator, GIS, Jupyter, ChatGPT, pylint, Apache Beam, Apache Airflow, Cloud Dataflow, Google Analytics, BigQuery, Vim Text Editor, Boto, AWS IAM, GeoNames, ANTLR, RabbitMQ, Celery, Scikit-image, Amazon Elastic Container Service (ECS), Docker Hub, Docker Compose, uWSGI, AutoCAD, AWS Fargate, Visual Language Models (VLMs), Claude, n8n
Languages
Python 3, SQL, Python, C++, Cypher, C++17, GraphQL, Java SE (Core Java), HTML, Bash, Java, C, Objective-C, C++14, Bash Script
Paradigms
Object-oriented Programming (OOP), Test-driven Development (TDD), Unit Testing, Back-end Architecture, ETL, DevOps, Agile, Microservices, REST
Platforms
Docker, Google Cloud Platform (GCP), Amazon Web Services (AWS), Amazon EC2, Linux, Web, AWS Lambda, Kubernetes, Azure
Storage
Databases, Relational Databases, Data Pipelines, PostgreSQL, Google Cloud, Amazon S3 (AWS S3), Neo4j, MySQL, Redis, MongoDB
Frameworks
Flask, Google Test, WebObjects, Enterprise Objects Framework (EOF), gRPC
Industry Expertise
Project Management
Other
Artificial Intelligence (AI), Clustering, Convolutional Neural Networks (CNNs), Image Processing, Data Analytics, Recommendation Systems, Data Analysis, Data Science, Computer Vision, Natural Language Processing (NLP), Deep Learning, Machine Learning, Data Visualization, Object Detection, Machine Learning Operations (MLOps), Data, Analytics, Large Language Models (LLMs), Computer Vision Algorithms, Data Engineering, Neural Networks, Predictive Modeling, Back-end, Generative Pre-trained Transformers (GPT), Graphics Processing Unit (GPU), Multithreading, Embeddings from Language Models (ELMo), Cloud Infrastructure, Object Recognition, Image Manipulation, Generative Artificial Intelligence (GenAI), Communication, AI Pipeline, Vector Databases, Architecture, Solution Architecture, Model Deployment, AI Tools, OpenAI, Deployment, Workflow Automation, Image Segmentation, APIs, Search, Algorithms, Cython, Concurrency, Multiprocessing, GraphDB, Computer Graphics, Product Leadership, Big Data, Technology Consulting, Object Tracking, Search Engines, Data Modeling, Data Extraction, API Documentation, Cloud, CI/CD Pipelines, Language Models, Fine-tuning, Chatbots, Infrastructure, Application Performance Monitoring, Prompt Engineering, Retrieval-augmented Generation (RAG), Agentic AI, OAuth, AI Agents, Local Hosting, Open-source LLMs, Document Parsing, Vector Search, Google Data Studio, Google Cloud Functions, Google BigQuery, Heuristics, Genetic Algorithms, Image Search, Objects, Storage, Optical Character Recognition (OCR), Compilers, ARM, Geospatial Data, Point Clouds, User Behavior, Serverless, API Integration, Open Source, Statistics, Causal Inference, Data Inference, Text Generation, Scripting, Video Processing, Revenue Optimization, Pricing Strategy, OpenAI GPT-4 API, Abstract Syntax Trees (AST), Azure AI Document Intelligence, Rendering, LangChain
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