Jorge Alberto Becerra

jorge (at) koruke (dot) comlinkedin.com/in/bvlqz

Machine Learning Engineer with 5+ years developing scalable simulation systems and production software. Proven track record in microservices architecture, CI/CD optimization, and cross-functional collaboration. Multiple patents in additive manufacturing.

Patents & Publications

  • -Innovator Award by HP Inc — Awarded in 2024 for a confidential invention reviewed and recognized by the patent committee.
  • -Publication — Additive Manufacturing, Vol. 110 (2025): "A calibration method to predict shape change during sintering: Application to 316L parts made by Metal Binder Jetting"[doi: 10.1016/j.addma.2025.104938]
  • -Modifying a Geometry of a Modeled Part — Patent Application filed Jan 11, 2024.[WO2025151122]
  • -Iterative Model Compensation — Patent Application filed Apr 21, 2021.[US20240184954A1]
  • -Object Packing Genetic Procedures — Patent Application filed Dec 14, 2020.[US20230401357A1]

Experience

HP Inc — HP Additive Manufacturing Solutions

Machine Learning Engineer II

November 2023 - August 2025

  • -HP Digital Production Suite — Productized R&D prototypes into scalable microservices, enabling commercial launch of 3D printing optimization tools. Collaborated with cross-functional teams, driving deployment strategies from concept to production.
  • -HP 3D Build Optimizer — Developed backend components for automated nesting tool, reducing build costs by 20% and improving printer utilization by 21%. Built automation tooling and streamlined workflows, implementing testing and deployment pipelines.
  • -HP 3D Digital Sintering — Applied machine learning and black-box optimization algorithms to achieve 1% dimensional accuracy in deformation prediction software for metal 3D printers. Implemented automated parameter tuning workflows against 3D scan data.

HP Inc — HP Labs

Machine Learning Engineer I

November 2021 — October 2023

  • -Simulation Software Development — Developed simulation tools and compensation algorithms for metal and plastic 3D printing deformation prediction, through physics-based model calibration against 3D scan data and high-volume validation.
  • -Software Architecture — Contributed to geometry processing engines and simulation workflows in C++ and Python, bridging physical manufacturing processes with digital modeling systems.
  • -DevOps Engineering — Reduced simulation software release cycle from hours to under 20 minutes by implementing CI/CD pipelines with Azure DevOps and Docker, enabling rapid deployment of production tools.
  • -High-Volume Simulation Framework — Built high-throughput simulation framework processing thousands of customer parts, implementing automated job queues and distributed computing across multiple nodes.
  • -Cross-Functional Team Leadership — Certified SAFe 5 Agilist. Led agile development initiatives across mechanical, materials, and software engineering teams, delivering integrated simulation capabilities.

HP Inc — HP Labs

Internship on Modeling and Numerical Simulation

April 2019 — October 2021

  • -R&D Contributions — Developed software to analyze physical processes in HP Multi Jet Fusion and Metal Jet systems, directly contributing to HP's intellectual property in additive manufacturing.
  • -Automation & Developer Tools — Implemented CI/CD pipelines (Jenkins) for in-house simulation software to reduce build/test cycles and developed GPU-accelerated visualization tools for 3D simulation data.

Skills

Programming Languages

Python, C++, JavaScript, Go, SQL, Racket

Technologies

Docker, Linux, Git, CMake, Azure DevOps, Jenkins, Kubernetes

Frameworks/Libraries

NumPy, VTK, Dealii, OpenCV, TensorFlow, SciPy, Gin

Extension Languages

Boost, TBB, OpenGL, CUDA, Eigen

Education

Universidad Tecmilenio

Bachelor of Engineering in Mechatronics

GPA 4.0 (95/100)

Graduated May 2022