Ben Epstein Email & Phone Number

Boston, Ma, Us

New York, New York, Us

Continuing to lead our LLM platform powering all product lines + MedHub, as well as various other initiatives.Acquired by CCC Intelligent Solutions

New York, New York, Us

We're on a mission to help more people get back to work using best in class machine learning techniques.I lead the design, development, and rollout of our LLM platform which now powers 100% of existing product lines and is a fundamental component of our next-generation MedHub product.

New York, New York, Us

Bilbao, Es

I co-host the bi-monthly MLOps workshops, where open-source contributors and industry leaders showcase amazing MLOps technology in live-coding sessions. https://www.youtube.com/c/MLOpscommunity/videos

San Francisco, Ca, Us

Bringing trustworthy resources to the MLOps landscape

San Francisco, California, Us

At least 80% of our data is unstructured. We're building an intelligence layer dedicated to understanding it. Galileo is working with ML teams from startups to Fortune 500s, across multiple industries.Employee #3, responsible for designing and scaling our ML platform architecture to manage large-scale embedding algorithms across modalities from text-classification to NER to Object detection and counting.

Sebastopol, Ca, Us

Co-authored and wrote the O'Reilly report "Accelerate Machine Learning with a Unified Analytics Architecture" https://www.oreilly.com/library/view/accelerate-machine-learning/9781098120313/

St. Louis, Mo, Us

Adjunct Professor for CSE427 - Cloud Computing and Big DataDesigned course from scratch to be taught to upperclassmen and graduate students. Content focused on Linux, Docker, Kubernetes, RDBMS, AWS (EC2, S3, EKS, IAM), Spark and Python.

San Francisco, California, Us

Machine Learning Lead for Splice Machine and product owner of MLManager, an end-to-end Machine Learning lifecycle management platform https://splicemachine.com/solutions/data-scientists, and our Feature StoreResponsible for:* Roadmapping and prioritization of Machine Learning product development* Technical lead for Machine learning product engineering* Hiring, on-boarding, and management of ML Interns* Machine Learning product marketing via website content and Medium articles* Machine Learning led sales* Machine Learning focused customer success projectsBrought feature store product from concept to market in under 1 year. Offers for purchase within year of market release.https://github.com/splicemachine/ml-workflow

San Francisco, California, Us

Design and build architecture to streamline Machine Learning model deployment and governance (MLManager)Develop and deploy Machine Learning algorithms for businesses, saving time and money using their existing data.Integrate new Machine Learning libraries and capabilities into Splice cloud infrastructure.Train new businesses on using our scale-out database and data science platform for transactional and analytical data processing.Manage recruiting, hiring, and training for Machine Learning and Data Science Interns.Oversee and lead projects for ML and Data Science Interns, including weekly meetings to ensure deliverables are met, and project management for all data science projects.Contribute to the marketing of the MLManager product, including writing articles, documentation, and creating training videos on YouTube.

Instructed more than 200 students in the fundamentals of Java and computer science using Sedgewick’s Java API and common data structuresAdvance students’ computer science skills with finite state machines, microcontrollers, Arduinos, cross platform communication, and information representation using Java and Arduino CTeach LAMP stack through numerous personal projects such as live chat rooms, AJAX calendars and file sharing sites

Utilized data science and big data to determine, detect and prevent cyber criminals from laundering money via Point of Sales and Account Takeover attacksAnalyzed decision trees to find features that most accurately predicted fraudulent activity Designed and built multiple machine learning algorithms including Random Forests and Deep Neural Networks using PySpark and H2O to more quickly and accurately detect attacks.Helped migrate team's environment from terminal based execution to Anaconda/Jupyter notebooks for quicker development, debugging and deployment

San Francisco, California, Us

Successfully merged eleven pull requests into codebase over 3 repositoriesDesigned and built autocompleter for Apache Zeppelin SQL server on Splice MachineCreated JMX MBean server for monitoring and reporting cache and memory data for VisaIncreased Splice Machine’s SQL dialect with support for greater type conversion and conditional statementsDeveloped Python package to support native Java-based Splice Machine connection using Py4J for use in data science and machine learning

Greenville, Texas, Us

Team coder. Competed at local and state level. Qualified and competed in World competition with nearly 800 teams

Bachelor Of Science (B.S.), Computer Science

High School