Josh Hamet

Block ML Platform Tech Lead / Staff Machine Learning Engineer

Block

Jul 2023 - Current (3 years 3 months)

• 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

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 le

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 ranki

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 f

About

Detail

Timeline

Résumé

Josh Hamet

About

Detail

Behavioral traits