Montreal, Canada

Ilhan
Esmail

Additive Manufacturing Engineering Manager
Product Design · 3D-printing · Aerospace · Process Development

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Ilhan Esmail

About

Engineering useful things,
one layer at a time.

I'm an engineering leader focused on scaling industrial additive manufacturing through materials science and data-driven process design. At AON3D, I lead the Applications Engineering and Customer Success teams, while leading slicer product development and creating print processes improvements for high-performance polymer systems used across aerospace, defence, and healthcare.

My work bridges strategy and execution—from building engineering teams and customer enablement systems to hands-on design, slicing, and mechanical validation. I've delivered flight-qualified parts for the International Space Station in collaboration with NASA and CSA, reduced project lead times by up to 50% through operational improvements, and developed materials validation frameworks that enable more reliable, data-driven printing. I also occasionally run deep learning workshops at McGill University, my alma mater.

220%
Toughness increase via bio-inspired ceramic manufacturing process
53%
Reduction in manufacturing & product development lead time via JIRA & Git process automation
70%
Faster mechanical test analysis via Python automation across NRC labs
ISS
Parts produced for the International Space Station with NASA & CSA

Experience

Where I've worked

Applications Engineering Manager

AON3D, Montreal YC · Series A
  • Led end-to-end manufacturing process development for AON3D's new industrial 3D printing product line — defining process parameters, consumables, and secondary operations to meet dimensional, cosmetic, and functional specifications.
  • Designed and implemented a filament validation & qualification framework — integrating material characterisation, embedded sensor data, and AI-driven analytics to produce repeatable, high-yield print profiles analogous to IQ/OQ/PQ methodology.
  • Drove process optimisation using hands-on DOE approaches, reducing project lead time from 30 → 14 days by redesigning workflows and establishing data-driven validation methods.
  • Collaborated with enterprise customers and supply partners across the US and Canada to align manufacturing development strategies with design requirements, conducting on-site process qualification and root-cause analysis.
  • Built and operated an internal print farm supporting sample production and process optimisation — directly analogous to managing a pilot manufacturing line during product ramp.
  • Developed applications discovery programmes and strategic partnerships, including additive manufacturing projects producing flight-qualified parts for the International Space Station with NASA & CSA.
  • Scaled the Applications Engineering organisation 2×, establishing cross-functional processes that earned recognition as a top support organisation in the additive manufacturing industry.
Process Development DOE Team Leadership AM Qualification AI Analytics

Additive Manufacturing & Materials Specialist

AON3D, Montreal
  • Developed and executed material characterisation and quality testing protocols for low- and high-temperature polymer systems, including tensile and shear studies to validate in-application mechanical properties.
  • Optimised print process parameters for high-performance thermoplastic filaments — building calibration test suites to define and document settings, consumables, and secondary operations per material and geometry requirement.
  • Produced technical content translating complex materials science into actionable manufacturing guidance, increasing customer adoption and website engagement by 127%.
Materials Characterisation Process Optimisation High-Perf. Polymers

Deep Learning / AI Instructor

McGill University, Montreal
  • Delivered 3 introductory workshops on deep learning (Autoencoders & CNNs) for the next generation of engineers and scientists.
Deep Learning CNNs Teaching

Aerospace Materials Researcher

National Research Council Canada (NRC-CNRC), Montreal
  • Built a CNN-based classification system (OpenCV + TensorFlow) to identify biological microstructures, enabling fabrication of bio-inspired ceramics with a 220% increase in toughness.
  • Pioneered bio-inspired ceramic manufacturing techniques — including forming, sintering, and microstructural optimisation — published as a peer-reviewed first-author article, one of the youngest at NRC to achieve this.
  • Created an ANSYS FEA simulation to validate temperature-dependent deformation of carbon nanotube composites for smart robotics applications in collaboration with the University of Toronto.
  • Wrote Python automation for tensile and quasi-static mechanical testing, reducing data analysis time by 70% across NRC labs in Montreal and Ottawa.
  • Delivered four research projects in one year, coordinating cross-functional teams and producing government grant documentation on schedule.
CNN / TensorFlow ANSYS FEA Ceramics Python Automation Research

Skills

Tools & technologies

Additive Manufacturing

FFF / FDM Metal AM Powder Metallurgy Process Qualification Slicing & G-code

Engineering & Design

SolidWorks Fusion 360 ANSYS FEA

Data & Automation

Python TensorFlow OpenCV Claude Code Git

Materials

High-Perf. Polymers Ceramics Composites Tensile / Shear Testing

Education

Academic background

2016 — 2021

McGill University

B.Eng. Materials Engineering Co-op
Minor — Aerospace Engineering
CGPA 3.80 / 4.00
Jun — Jul 2021

MIT

Fellowship — Multiscale Materials Design
Machine Learning & AI for 3D-printed design optimisation

Languages

English Native
French Intermediate
Hindi Intermediate

Blog

Writing & thinking

All Posts

Contact

Let's talk.

Open to research collaborations, consulting engagements, and conversations about advanced manufacturing and materials.