Pablo Ibarra
Senior Machine Learning Engineer at Mavenoid
Oregon, Spain
Summary
👤
Senior🎓
Top SchoolPablo Ibarra is a Senior Machine Learning Engineer with nine years of experience building production-grade ML systems that improve user experiences. Currently at Mavenoid in Oregon, he designs retrieval and generative AI solutions—fine-tuning LLMs, parsing and encoding PDFs for semantic search, and deploying Dockerized MLOps pipelines on GCP. His background spans fintech and ecommerce risk modeling at Returnly and Affirm, plus consulting projects in document OCR, demand forecasting, and churn analysis using tools from LightGBM and PySpark to transfer-learned CNNs. He combines hands-on model development with end-to-end engineering—vector databases, CI/CD, experiment tracking, and integration testing—to move prototypes into robust services. A former freelance Python trainer, he also brings practical pedagogy to complex topics, making advanced ML accessible to teams. Trained in Mathematical Engineering, he pairs strong quantitative foundations with a pragmatic focus on scalable, interpretable solutions.
9 years of coding experience
5 years of employment as a software developer
CourseraMathematical Engineering, Specialized in Economathematics, Mathematical Engineering, Specialized in Economathematics at Complutense University of Madrid
English, Spanish
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (15)
shapley10
shap10
gradient-boosting10
machine-learning9
deep-learning9
machine-learning-models8
pdf3
python-data2
jupyter-notebook2
bayesian-methods1
reinforcement-learning1
sklearn1
hyperparameter-tuning1
mlflow1
bag1
Programming languages (1)
Github contributions (5)
pablo-var/TFG_ML_Exercises
Aug 2017 - Jan 2019
Contributions:67 commits, 58 pushes, 1 branch in 1 year 4 months
pablo-var/sk-ml-pipeline
Feb 2020 - Apr 2020
End-to-end sklearn model training, hyperparameter tuning, experiment tracking, and deployment using mlflow
Contributions:2 PRs, 16 pushes, 4 branches in 1 month
hyperparameter-tuningmlflowsklearn
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