julio@zambrano: ~/portfolio
julio@zambrano:~$ whoami

AI/ML engineering, built for production — not just a pilot.

15+ years of engineering experience across Mexico, Canada, Italy, Austria, and Germany, spent turning machine learning, generative AI, and cloud architecture into systems that hold up outside a notebook.

julio-zambrano.jpg
Portrait of Julio Zambrano
profile.yaml
location: Baden-Württemberg, Germany
focus: [Machine Learning, Generative AI, Cloud Architecture]
languages: [ES, EN, PT, IT, DE]
status: open_to_ai_ml_roles
julio@zambrano:~$ cat about.md

Julio started as a mechatronics engineer and moved into machine learning through hands-on production work: deploying generative AI and synthetic data systems for enterprise customers, running multi-cloud infrastructure on AWS, Azure, and GCP, and building models in TensorFlow and H2O for real client problems, from predictive maintenance on robotic arms to production ML pipelines. He's published applied research in NLP and predictive maintenance, and has worked across five countries in roles that combined deep technical build-out with enterprise-scale deployment. He's now looking for a hands-on AI/ML engineering role — building and scaling systems, not just advising on them.

tags: Machine Learning, Generative AI, Synthetic Data, Multi-Cloud Architecture, Kubernetes & OpenShift, Applied NLP
julio@zambrano:~$ cat experience.log
2025-11 — present

Technical Customer Success Manager

Camunda · remote (Tannheim, DE)
  • Architect agentic orchestration solutions for enterprise clients, from use-case validation through implementation and ongoing optimization.
  • Design deployment architecture across SaaS, cloud, hybrid, and self-managed environments, including air-gapped infrastructure for regulated industries.
  • Lead technical architecture reviews and onboarding to drive platform adoption for enterprise accounts.
2022-03 — 2025-10

Customer Experience Engineer

MOSTLY AI · remote (Vienna, AT)
  • Architected multi-cloud infrastructure (AWS, Azure, GCP) for generative AI and synthetic data deployments across customer environments.
  • Standardized deployment pipelines for a generative AI application to support product-led growth.
  • Deployed and troubleshot applications on Kubernetes and OpenShift; built technical enablement materials for engineering and customer teams.
2020-08 — 2022-03

Machine Learning Engineer, Freelance

jzambrano.xyz · remote
  • Gathered requirements and built logical and physical system specifications for client machine learning projects.
  • Researched, designed, and tested ML/AI models using TensorFlow and H2O for production use cases.
  • Managed multi-cloud infrastructure (Azure, GCP): monitoring, cost and availability reporting, virtualization, containerization.
2021-02 — 2021-10

Junior Machine Learning Engineer, Internship

CENIDET · Cuernavaca, MX
  • Developed a machine learning model for preventive maintenance of palletizing robotic arms (cobots).
  • Built data and process models to optimize architecture and evaluate design performance and reliability.

earlier international management experience (sales, operations) is on the full résumé

julio@zambrano:~$ cat skills.json
skills.json
{
"ml_ai": ["TensorFlow", "H2O", "generative AI", "synthetic data", "agentic orchestration"],
"cloud_infra": ["AWS", "Azure", "Google Cloud", "Kubernetes", "OpenShift"],
"certifications": [
"AWS Cloud Quest: Data Analytics, ML, Solutions Architect",
"Google Cloud: Core Infrastructure, DevOps",
"Kubernetes Fundamentals — Linux Foundation"
],
"languages": // native, C1, C1, B2, B1
["Spanish", "English", "Portuguese", "Italian", "German"]
}
julio@zambrano:~$ cat publications.bib
@inproceedings — Cuéllar-Hidalgo, Guerrero-Zambrano, et al. Multilingual gender-biased and communal language identification without linguistic features, for the LUC team's ComMA-2021 shared task submission.
# 18th International Conference on Natural Language Processing · Dec 2021 · Silchar, India
@inproceedings — Guerrero-Zambrano, Reyes-Salgado. A comparison of machine learning algorithms for the preventive diagnosis of palletizing robotic arms.
# CINIAI 2021 — Congreso Internacional de Inteligencia Artificial e Industria 4.0 · Nov 2021 · Jalisco, Mexico