About

I am an industrial engineer and systems-oriented generalist with particular depth in applied AI evaluation, deployment and end-to-end product engineering.


Yago Mendoza | Industrial engineer and applied AI engineer

I am an industrial engineer and systems-oriented generalist with particular depth in applied AI evaluation, deployment and end-to-end product engineering.

I use that breadth to connect domain, software and infrastructure constraints, structure ambiguous problems and build systems that work in practice.

Selected evidence:

70 → 93%: DxGPT evaluated diagnostic accuracy, improved through model selection, inference optimization and safety guardrails.

≈700K: Queries per year served by the clinical AI system supported by that evaluation capability.

0 → shipped: TrialGPT built end to end: document parsing, clinical extraction, matching, evaluation, UX, backend and Azure deployment.

Core capabilities:

- AI evaluation & model selection

- Production deployment & reliability

- End-to-end product engineering

- Systems integration under operational constraints

Experience:

Fundación 29 de Febrero | Applied AI Engineer | 2025 – Present

Building and operating clinical AI systems where model behavior requires measurable evidence, resilient infrastructure and human review.

- Built the organization’s first GenAI evaluation capability for model-selection and ship/no-ship decisions.

- Helped improve DxGPT’s evaluated diagnostic accuracy from approximately 70% to 93%.

- Built and shipped TrialGPT end to end, from medical-document parsing to evaluation, UX, backend and Azure deployment.

Leadrank | Product Engineer · Independent | 2026 – Present

Building an AI product that turns unstructured email history into structured commercial intelligence for real-estate workflows.

- Designed ingestion and extraction for historical and real-time email processing.

- Built entity resolution and matching across contacts, deals, buyer intent and properties.

- Validating workflows and product demand with agents in Barcelona and Madrid.

UNE | AI Standards Committee · Independent | 2026

Participated independently in Spain’s mirror committee for European and international AI standardization.

- Contributed through UNE CTN 71/SC 42 committee meetings and standards review.

- Studied evaluation, bias management, dataset quality, risk and conformity-assessment workflows.

Sony Europe | ML & Distributed Systems Engineer | 2024

Worked inside Sony Europe’s Brussels ML R&D lab across blockchain optimization, program synthesis and agent evaluation.

- Designed execution-based agent evaluation using compilation, automated tests and network deployment.

- Took the research system end to end, from DSPy and LangChain experiments to orchestration and infrastructure.

- Operated the Hyperledger Besu network, SDK and monitoring stack; selected optimizations entered Sony’s work.

TE Connectivity | Supply Chain Data & Automation Intern | 2023

Applied software and data engineering to operational supply-chain processes.

- Automated inventory, CRM and bill-of-materials reporting with Python and SQL.

- Built internal pipelines and reporting tools to improve data quality and planning visibility.

CIMNE | Safety Engineering · EU LASH FIRE | Earlier

Worked on safety-critical engineering within the EU-funded LASH FIRE research project.

- Contributed industrial engineering analysis where technical decisions met physical safety constraints.

Selected work:

- TrialGPT: from a medical report to a shortlist of eligible trials: A clinical-trial matching tool built at Foundation 29: describe your case or upload a report, and TrialGPT finds relevant trials near you in ClinicalTrials.gov and the European CTIS register, checks the inclusion and exclusion criteria against your situation clause by clause, and drafts a message to the trial coordinator. Covers the 2025 build, its eligibility reasoner and its failure modes, and how the live product works a year on. (https://infraphysics.net/lab/projects/trialgpt-clinical-trial-matching)

- Model-based fault detection in a two-tank system: Model-based fault detection and isolation on a two-tank hydraulic plant under closed-loop control. Thirteen component relations are reduced by structural analysis to four analytical redundancy relations, evaluated as residuals on Simulink runs, thresholded on healthy data and matched against a fault-signature matrix. Covers detectability and isolability, the noise cost of differentiating level measurements, the failure of exact signature matching, and the calibration a physical installation would require. (https://infraphysics.net/blog/bits2bricks/two-tank-fault-detection)

- A CRM for a health-tech startup, built solo in 72 hours: A bespoke CRM for a health-tech startup, designed and shipped solo in 72 hours. A real product built as an experiment in AI-assisted engineering: 23 tables, 8 state machines, automated enrichment and stale-relationship detection. (https://infraphysics.net/lab/projects/health-tech-crm)

- Building this site: a markdown compiler, a theme system and a second brain: How a systems engineer built a personal site with a custom markdown compiler, a second brain, and an AI development partner (and what went wrong along the way). (https://infraphysics.net/lab/projects/building-infraphysics)

- Transformers from scratch: A patient, ground-up explanation of transformer architecture: how tokens become predictions, what attention really computes, where facts live, and why it all scales. (https://infraphysics.net/blog/bits2bricks/transformers-from-scratch)

Contact: [email protected]