Matthew is available for hire
Hire MatthewMatthew Warkentin
Verified Expert in Engineering
Machine Learning Engineer and Developer
San Francisco, CA, United States
Toptal member since March 8, 2019
Bio
Since 2014, Matthew has been working professionally in the fields he loves, software and data—culminating in him co-founding the Rubota corporation in 2017. Before that, he spent the past decade at Cornell University conducting scientific research specifically in statistical and biological physics. All in all, Matthew is an engaging, intense communicator with a passion for knowledge and understanding.
Portfolio
Toptal Client
Analytics, Data Analysis, Business Requirements, Data Pipelines, SQL...
Toptal Client
Artificial Intelligence (AI), Natural Language Processing (NLP)...
Toptal Client
Artificial Intelligence (AI), Natural Language Processing (NLP)...
Experience
- Statistics - 20 years
- Modeling - 20 years
- Data Engineering - 20 years
- Artificial Intelligence (AI) - 10 years
- Machine Learning - 10 years
- SQL - 10 years
- AI Model Training - 5 years
- Data Science - 5 years
Work Experience
VP | Data and Analytics
2020 - PRESENT
Toptal Client
- Built a world-class data and analytics function to handle hundreds of millions of user interactions covering infrastructure, warehousing, reporting/dashboards, real-time graph-based recommendations, propensity models, in-app search, and automated QA.
- Managed over 10x user growth accompanying the launch of strategic partnership.
- Supported the decision-making for 4-6 projects or product features per quarter in engineering, product, marketing, and finance.
- Developed a real-time computer vision system for officiating match play in live streams using multimodal LLMs.
Technologies: Analytics, Data Analysis, Business Requirements, Data Pipelines, SQL, Computer Vision, Machine Learning, Optimization, AI Model Training, Data Science, Linux, Statistics, Modeling, Visualization, Data Engineering, Google Cloud Platform (GCP), Artificial Intelligence (AI), PyTorch, Hugging Face, Open-source LLMs, Prompt Engineering, Multimodal GenAI, Multimodal Models, Retrieval-augmented Generation (RAG), Machine Learning Operations (MLOps), NumPy, Ubuntu
AI Engineer/Consultant (via Toptal)
2024 - 2024
Toptal Client
- Consulted on next-generation AI features using chat to interact with documents, slides, and spreadsheets at the management/investor level.
- Developed and deployed containerized services to deliver these features and standalone interfaces for rapid iteration.
- Built proofs of concept for slide and presentation creation, spreadsheet reading, summarizing, editing, and consistency checking.
Technologies: Artificial Intelligence (AI), Natural Language Processing (NLP), Machine Learning, Large Language Models (LLMs), LangChain, Hugging Face, Prompt Engineering, Machine Learning Operations (MLOps), NumPy, Ubuntu
AI Engineer/Consultant (via Toptal)
2024 - 2024
Toptal Client
- Provided a roadmap to develop AI features from concept to MVP, including architecture, integration, infrastructure, LLM model selection, feedback and training, and cost/quality trade-offs.
- Built fully functioning proof of concept using example data from the client. The proof of concept demonstrated user interactions with product and design and integration to engineering to de-risk estimates.
- Gathered and integrated considerations across functions, including engineering, product, and fundraising.
Technologies: Artificial Intelligence (AI), Natural Language Processing (NLP), Large Language Models (LLMs), Minimum Viable Product (MVP), Machine Learning, Technical Leadership, Architecture, Software Architecture, LangChain, PyTorch, Hugging Face, Open-source LLMs, Prompt Engineering, Machine Learning Operations (MLOps), NumPy, Ubuntu
Data Scientist (Generalist)
2019 - 2020
Toptal Client
- Developed end-to-end marketing data and analytics solution, covering scraping, fusion, predictive modeling, deployment, reporting, and evaluation.
- Completed studies and proofs of concept for company leadership and regularly advised at that level.
- Built a hybrid statistical/NLP model for the impact of online reviews.
- Created a qualitative analysis framework to develop coding schemes for survey responses.
- Developed a predictive model for an all-in cost of delivery using years of historical data.
- Built prototype eCommerce pricing and UX model based on years of historical sales data. Spun out with multiple rounds raised.
Technologies: Amazon Web Services (AWS), SQL, Python, Pricing Models, Data Analysis, Business Requirements, Data Pipelines, Machine Learning, Optimization, AI Model Training, Data Science, Linux, Statistics, Modeling, Visualization, Data Engineering, Analytics, Artificial Intelligence (AI), Machine Learning Operations (MLOps), NumPy, Ubuntu
Co-founder | Vice President of Data and Analytics
2017 - 2019
Rubota Corporation
- Collected and integrated data from disparate sources into a unified model.
- Worked with the chief engineer to develop a platform data model.
- Integrated in-house and third-party entity analytics.
Technologies: Machine Learning, Python, Data Pipelines, Data Science, Linux, Statistics, Modeling, Visualization, Data Engineering, Data Analysis, Business Requirements, SQL, Analytics, Artificial Intelligence (AI), NumPy, Ubuntu
Data Scientist
2014 - 2016
Thetus Corporation
- Produced prototypes and handled third-party integrations.
- Engaged with customers to understand their data and applications.
- Supported sales and marketing with demonstrations tailored to target customers.
- Led the analysis team supporting sales to industry clients.
Technologies: Amazon Web Services (AWS), Python, Data Analysis, Business Requirements, Data Pipelines, Data Science, Linux, Statistics, Modeling, Visualization, Data Engineering, Optimization, SQL, Analytics, Machine Learning, Artificial Intelligence (AI), NumPy, Ubuntu
Postdoctoral Researcher
2009 - 2014
Cornell University
- Authored eight peer-reviewed studies in X-ray science, structural biology, and statistical mechanics.
- Developed novel analytical and visualization tools to investigate protein conformational motions.
- Managed the teams running experiments at Cornell's X-ray source and Argonne National Lab under extreme time pressure (typically 24 to 48 hours from start to finish).
- Built and maintained data pipelines to construct 3D models of macromolecules from thousands of X-ray images.
Technologies: Python, Data Analysis, Data Pipelines, Computer Vision, Machine Learning, Optimization, Data Science, Linux, Statistics, Modeling, Physics, Visualization, Data Engineering, Bioinformatics, NumPy, Ubuntu
Graduate Research Assistant
2004 - 2009
Cornell University
- Pioneered experimental techniques to exploit opportunities in the rapidly-evolving field of structural biology.
- Standardized and automated existing data collection and processing practices, resulting in a greatly increased impact on the final product.
- Managed undergraduate research projects, typically resulting in co-authorship on publications in international scientific journals.
Technologies: Linux, Python, Data Analysis, Data Pipelines, Computer Vision, Data Science, Statistics, Modeling, Physics, Visualization, Data Engineering, Optimization, Bioinformatics, NumPy, Ubuntu
Project History
Rubota Corporation
At Rubota, a supply chain intelligence technology startup, I served as the co-founder and VP of data and analytics. My primary focus was on developing unstructured analytics for integrated supply chain for an enterprise customer.
Education
2004 - 2009
PhD in Physics
Cornell University - Ithaca, NY, USA
2000 - 2004
Bachelor of Arts Degree in Physics
UCSC | University of California, Santa Cruz - Santa Cruz, CA, USA
Skills
Libraries/APIs
NumPy, PyTorch
Languages
SQL, Python
Platforms
Google Cloud Platform (GCP), Amazon Web Services (AWS), Linux, Ubuntu
Storage
Data Pipelines
Industry Expertise
Bioinformatics
Other
Data Engineering, Machine Learning, Statistics, Physics, Modeling, Data Analysis, Mathematics, Visualization, Data Science, Optimization, Computer Vision, Analytics, Business Requirements, AI Model Training, Artificial Intelligence (AI), Large Language Models (LLMs), Open-source LLMs, Prompt Engineering, Retrieval-augmented Generation (RAG), Machine Learning Operations (MLOps), Pricing Models, Natural Language Processing (NLP), Minimum Viable Product (MVP), Technical Leadership, Architecture, Software Architecture, LangChain, Hugging Face, Multimodal GenAI, Multimodal Models
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