Jeffrey Linsangan

I am a Mechanical Engineer with an MSc in Mechanical Engineering who bridges hands-on engineering diagnostics and modern data and AI evaluation workflows. I build reproducible, scriptable data pipelines (Python, pandas, CSV/JSON/YAML parsing) to turn noisy operational data into clear KPIs, automated reports, and test-banks used for model evaluation and engineering decision-making. My academic and practical training spans thermodynamics, heat transfer, fluid mechanics, solid mechanics, and CAD/FEA/CFD, which I combine with structured experimental design and root-cause analysis to deliver reliable, documented results.

Professionally, I have applied this hybrid skill set across two complementary domains. As a Digital Marketer and Social Media Analyst, I designed automated ad-performance reporting pipelines, implemented A/B tests to improve campaign ROI, and produced weekly dashboards and reproducible reporting templates for stakeholders. These projects sharpened my metric-driven approach to experiments, data cleaning, and stakeholder communication. In engineering roles, I conducted systematic subsystem troubleshooting, measurement-led inspections, and technical reporting, experience that enforces discipline in measurement, validation, and safety-critical documentation.

I have also led focused projects that demonstrate my ability to combine simulation, ML, and evaluation. I developed a CFD surrogate workflow to accelerate parametric heat-exchanger design (mesh sensitivity checks, surrogate RMSE validation). I created an LLM-based engineering Q&A evaluation suite, including a 40+ scenario test bank, gold-standard answers, and Python utilities for batch-running prompts and flagging inconsistencies. These projects reflect my interest in safe, measurable ways to integrate AI into engineering workflows, especially evaluation, guardrails, and failure-mode documentation.

What you can expect from me is rigorous test-case thinking, clear technical writing, and the ability to translate domain constraints into measurable evaluation criteria. I am seeking roles, ideally remote, full-time, part-time, or contract engagements, where structured evaluation and reproducible reporting are valued.