Josh Hamet

Block ML Platform Tech Lead / Staff Machine Learning Engineer

Block

Jul 2023 - Current (3 years 1 month)

• Lead the architecture and development of scalable machine learning platforms used by engineering teams for training, evaluating, and deploying production-grade AI models. • Design and implement distributed ML pipelines using Python and machine learning frameworks including PyTorch, TensorFlow, Keras, Scikit-Learn, XGBoost, LightGBM, and Spark MLlib. • Develop advanced Large Language Model (LLM) solutions including conversational AI systems, enterprise chatbots, document understanding pipelines, and AI-powered developer productivity tools. • Build scalable Natural Language Processing (NLP) pipelines using Hugging Face Transformers, spaCy, NLTK, Gensim, and OpenNLP for tasks such as entity recognition, sentiment analysis, semantic search, a

Senior Machine Learning Engineer / Machine Learning Engineer II

Twitter

Mar 2019 - Jul 2023 (4 years 5 months)

• Designed and optimized a distributed machine learning experimentation platform supporting thousands of engineers using Jupyter Notebook and Python-based ML environments. • Engineered a high-performance virtual file system for ML workflows, improving I/O operations and accelerating machine learning development cycles. • Built scalable machine learning models using PyTorch, TensorFlow, Keras, Scikit-Learn, XGBoost, and LightGBM for prediction, ranking, and recommendation tasks. • Developed Python-based backend systems and microservices using FastAPI and Flask, exposing machine learning models via RESTful APIs for internal applications and production services. • Designed large-scale NLP systems leveraging transformer-based models such as BER

Senior Software Engineer / Software Engineer II-III

Criteo

Nov 2016 - Mar 2019 (2 years 5 months)

• Designed and deployed a content-based logistic regression model using TensorFlow and Scikit-Learn to predict the relevance of search term-to-product associations in advertising systems. • Developed large-scale machine learning pipelines using Python and frameworks such as PyTorch, TensorFlow, Keras, and Spark MLlib to train predictive advertising models. • Implemented Python-based backend services using frameworks such as Flask and Django, exposing machine learning functionality through scalable RESTful APIs. • Built distributed data pipelines using Apache Spark and Hadoop to process billions of user interaction records for machine learning training datasets. • Designed recommendation and ranking algorithms using gradient boosting models,

H

Software Engineer

HookLogic (Acquired by Criteo)

Jul 2015 - Nov 2016 (1 year 5 months)

• Developed software solutions for a large-scale e-commerce advertising platform using Python and JavaScript, enabling retailers to integrate sponsored product recommendation systems. • Built backend services using Python frameworks such as Flask and Django to support scalable RESTful APIs used by advertising and analytics platforms. • Implemented distributed ETL pipelines using Hadoop MapReduce and Apache Spark to process large datasets of product information from multiple retail partners. • Developed feature engineering pipelines that generated training data for machine learning models used in advertising optimization systems. • Implemented data transformation systems to normalize product metadata from multiple schema formats. • Built mac

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