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Bentley Systems

Applied AI Engineer - Engineering Simulation & Design Exploration

Quebec, QC, Canada
Greater Quebec City Metropolitan Area, Canada

Job type: Full-time
Workplace: Hybrid
Apply by: Oct 31, 2026
Posting language: English · French
Posted: Oct 1, 2026

Apply About employer

Applications open in a new tab.

Original job description

English section of this bilingual listing.

Applied AI Engineer – Engineering Simulation & Design Exploration

Location: Quebec (Hybrid) - 3 days a week in office

About The Role

Engineering simulation is undergoing a structural shift. What used to be a slow, solver-driven process is becoming a fast, exploration-driven workflow, enabled by surrogate models, physics-informed AI, and GPU-accelerated methods.

This changes not just how simulations run, but how engineers design - moving from evaluating a few options to exploring entire design spaces.

We are looking for a hands-on Applied AI Engineer to experiment with these emerging technologies. Your role is to try new tools, test them, benchmark them, integrate them into prototypes, determine what actually works in practice, and give an informed decision on its viability in Bentley’s products. The goal is to develop a clear understanding of where these approaches can realistically transform engineering workflows - and where they cannot.

This is an experimental role. You will spend most of your time building and testing prototypes, not writing reports or maintaining production systems.

What You Will Do

Keep track of new technologies in the field
Evaluate emerging simulation and AI tools through hands-on prototyping
Build and benchmark surrogate models against traditional FEM/CFD workflows
Test robustness, limitations, and failure modes of new approaches
Prototype hybrid pipelines (e.g., surrogate + high-fidelity validation)
Explore how these approaches can integrate into real engineering workflows
Report to stakeholders with clear recommendations

Requirements

What We Are Looking For

Strong programming ability (Python required)
Experience with PyTorch, JAX, or similar ML frameworks
Solid understanding of numerical simulation:
Familiarity with:

Highly Valued

Experience building experimental or research prototypes
Understanding of design space exploration (DOE, parameter studies, combinatorial optimization)
Exposure to physics-informed ML or scientific machine learning
Experience working with GPU or high-performance computing environments
Experience working with machine learning for physics simulations
Hands-on experience developing Multiphysics simulation code

Mindset

Hands-on, experimental, and comfortable working with incomplete tools
Curious but skeptical - focuses on what works, not what is claimed
Naturally tests limits and edge cases, not just happy paths
Thinks in terms of workflows and iteration loops, not isolated tools
Able to quickly move from idea → prototype → insight
Good business acumen; able to understand what brings value to Bentley

What Success Looks Like

You build prototypes that demonstrate new ways to accelerate design workflows
You identify where AI-based approaches are genuinely useful - and where they fail
You provide clear, evidence-based insights grounded in experiments, not assumptions

What We Offer

Step into a collaborative work environment where ideas flourish, and teamwork propels us forward towards shared success.
An attractive salary and benefits package.
Bentley Impact Day: take a day off from work to volunteer with an organization of your choice.
Celebrate milestone achievements and moments that matter through our colleague recognition award programs and our Bentley Achievers platform.
A commitment to inclusion, belonging and colleague wellbeing through global initiatives and resource groups.
Be part of a company committed to making a real difference by advancing the world’s infrastructure for better quality of life, where your contributions help build a more sustainable, connected, and resilient world. Discover our latest user success stories for an insight into our global impact.

Who We Are

Bentley Systems (Nasdaq: BSY) is the infrastructure engineering software company. We provide innovative software to advance the world’s infrastructure – sustaining both the global economy and environment. Our industry-leading software solutions are used by professionals, and organizations of every size, for the design, construction, and operations of roads and bridges, rail and transit, water and wastewater, public works and utilities, buildings and campuses, mining, and industrial facilities. Our offerings, powered by the iTwin Platform for infrastructure digital twins, include MicroStation and Bentley Open applications for modeling and simulation, Seequent’s software for geoprofessionals, and Bentley Infrastructure Cloud encompassing ProjectWise for project delivery, SYNCHRO for construction management, and AssetWise for asset operations. Bentley Systems’ 5,200 colleagues generate annual revenues of more than $1 billion in 194 countries.

Equal Opportunity Employer

Bentley is proud to be an equal opportunity employer and considers for employment all qualified applicants without regard to race, color, gender/gender identity, sexual orientation, disability, marital status, religion/belief, national origin, caste, age, or any other characteristic protected by local law or unrelated to job qualifications.

Read the full bilingual original

Applied AI Engineer – Engineering Simulation & Design Exploration

Location: Quebec (Hybrid) - 3 days a week in office

About The Role

Engineering simulation is undergoing a structural shift. What used to be a slow, solver-driven process is becoming a fast, exploration-driven workflow, enabled by surrogate models, physics-informed AI, and GPU-accelerated methods.

This changes not just how simulations run, but how engineers design - moving from evaluating a few options to exploring entire design spaces.

We are looking for a hands-on Applied AI Engineer to experiment with these emerging technologies. Your role is to try new tools, test them, benchmark them, integrate them into prototypes, determine what actually works in practice, and give an informed decision on its viability in Bentley’s products. The goal is to develop a clear understanding of where these approaches can realistically transform engineering workflows - and where they cannot.

This is an experimental role. You will spend most of your time building and testing prototypes, not writing reports or maintaining production systems.

What You Will Do

Keep track of new technologies in the field
Evaluate emerging simulation and AI tools through hands-on prototyping
Build and benchmark surrogate models against traditional FEM/CFD workflows
Test robustness, limitations, and failure modes of new approaches
Prototype hybrid pipelines (e.g., surrogate + high-fidelity validation)
Explore how these approaches can integrate into real engineering workflows
Report to stakeholders with clear recommendations

Requirements

What We Are Looking For

Strong programming ability (Python required)
Experience with PyTorch, JAX, or similar ML frameworks
Solid understanding of numerical simulation:

FEM, CFD, or multiphysics modeling

Familiarity with:

Deep learning, surrogate modeling, reduced-order models, or optimization workflows
Good communication skills and collaborative mindset

Highly Valued

Experience building experimental or research prototypes
Understanding of design space exploration (DOE, parameter studies, combinatorial optimization)
Exposure to physics-informed ML or scientific machine learning
Experience working with GPU or high-performance computing environments
Experience working with machine learning for physics simulations
Hands-on experience developing Multiphysics simulation code

Mindset

Hands-on, experimental, and comfortable working with incomplete tools
Curious but skeptical - focuses on what works, not what is claimed
Naturally tests limits and edge cases, not just happy paths
Thinks in terms of workflows and iteration loops, not isolated tools
Able to quickly move from idea → prototype → insight
Good business acumen; able to understand what brings value to Bentley

What Success Looks Like

You build prototypes that demonstrate new ways to accelerate design workflows
You identify where AI-based approaches are genuinely useful - and where they fail
You provide clear, evidence-based insights grounded in experiments, not assumptions

Ingénieur(e) en IA appliquée – Simulation d’ingénierie et exploration de conception

Lieu : Québec (hybride)

À propos du rôle

La simulation en ingénierie subit actuellement un changement structurel. Ce qui était auparavant un processus lent, axé sur les solveurs, devient un flux de travail rapide et axé sur l’exploration, rendu possible par les modèles de substitution (surrogate models), l’IA guidée par la physique (physics-informed AI) et les méthodes accélérées par processeur graphique (GPU).

Cette évolution change non seulement la façon d'exécuter les simulations, mais aussi la manière dont les ingénieurs conçoivent les projets, passant de l’évaluation limitée de quelques options à l’exploration de l’ensemble des espaces de conception.

Nous sommes à la recherche d’un(e) ingénieur(e) en IA appliquée pratique (hands-on) pour expérimenter ces technologies émergentes. Votre rôle consistera à essayer de nouveaux outils, à les tester, à les comparer (benchmarking), à les intégrer à des prototypes, à déterminer ce qui fonctionne en pratique et à prendre une décision éclairée quant à leur viabilité dans les produits de Bentley. L’objectif est de développer une compréhension claire de l’endroit où ces approches peuvent concrètement transformer les flux de travail en ingénierie - et de l’endroit où elles ne le peuvent pas.

Il s’agit d’un rôle à forte composante expérimentale. Vous passerez la majeure partie de votre temps à concevoir et à tester des prototypes, et non à rédiger des rapports ou à assurer la maintenance de systèmes de production.

Ce que vous ferez

Assurer une veille technologique sur les nouveautés dans le domaine.
Évaluer les outils émergents de simulation et d’IA par le biais du prototypage pratique.
Concevoir et comparer des modèles de substitution par rapport aux flux de travail traditionnels de FEM (méthode des éléments finis) et de CFD (dynamique des fluides numérique).
Tester la robustesse, les limites et les modes de défaillance des nouvelles approches.
Prototyper des pipelines hybrides (p. ex., modèle de substitution + validation haute fidélité).
Explorer comment intégrer ces approches dans de flux de travail d’ingénierie concrets.
Présenter des recommandations claires aux parties prenantes.

Ce que nous recherchons

Exigences

Fortes compétences en programmation (Python requis).
Expérience avec PyTorch, JAX ou d’autres frameworks d’apprentissage automatique similaires.
Solide compréhension de la simulation numérique :

Modélisation par FEM, CFD ou modélisation multiphysique.

Connaissance pratique de :

L’apprentissage profond (deep learning), de la modélisation de substitution, des modèles d’ordre réduit ou des flux de travail d’optimisation.

Bonnes compétences en communication et esprit de collaboration.

Atouts majeurs

Expérience dans la création de prototypes expérimentaux ou de recherche.
Compréhension de l’exploration de l’espace de conception (plans d’expériences [DOE], études paramétriques, optimisation combinatoire).
Exposition à l’apprentissage automatique guidé par la physique (physics-informed ML) ou à l’apprentissage automatique scientifique (scientific ML).
Expérience de travail avec des environnements GPU ou calcul haute performance (HPC).
Expérience dans l’application de l’apprentissage automatique aux simulations physiques.
Expérience pratique du développement de codes de simulation multiphysique.

Mentalité

Approche pratique, expérimentale et aisance à travailler avec des outils de développement incomplets.
Curiosité teintée de scepticisme - vous vous concentrez sur ce qui fonctionne réellement, et non sur les promesses marketing.
Propension naturelle à tester les limites et les cas particuliers (edge cases), et non seulement les scénarios idéaux.
Réflexion axée sur les flux de travail et les boucles d’itération, plutôt que sur des outils isolés.
Capacité à passer rapidement d’une idée → un prototype → des apprentissages concrets.
Bon sens des affaires; capacité à comprendre ce qui apporte de la valeur à Bentley.

À quoi ressemble le succès dans ce rôle

Vous concevez des prototypes qui démontrent de nouvelles façons d’accélérer les flux de travail de conception.
Vous identifiez les domaines dans lesquels les approches basées sur l’IA sont véritablement utiles - et ceux où elles échouent.
Vous fournissez des perspectives claires et factuelles, basées sur des expériences concrètes et non sur des hypothèses.

This is a Hybrid role.

What We Offer

Step into a collaborative work environment where ideas flourish, and teamwork propels us forward towards shared success.
An attractive salary and benefits package.
Bentley Impact Day: take a day off from work to volunteer with an organization of your choice.
Celebrate milestone achievements and moments that matter through our colleague recognition award programs and our Bentley Achievers platform.
A commitment to inclusion, belonging and colleague wellbeing through global initiatives and resource groups.
Be part of a company committed to making a real difference by advancing the world’s infrastructure for better quality of life, where your contributions help build a more sustainable, connected, and resilient world. Discover our latest user success stories for an insight into our global impact.

Apply About employer

More about this job

Responsibilities

Build and benchmark experimental prototypes using emerging AI and simulation technologies, including surrogate models and hybrid pipelines, and test their robustness, limitations, and failure modes. Assess how these approaches could fit real engineering workflows and provide stakeholders with clear, evidence-based recommendations about their viability in Bentley products.

Requirements

Requires strong Python programming skills, experience with PyTorch, JAX, or similar machine-learning frameworks, and a solid understanding of numerical simulation such as FEM, CFD, or multiphysics modeling. Familiarity with deep learning, surrogate or reduced-order models, or optimization workflows is expected; experience with research prototypes, design space exploration, physics-informed ML, GPU/HPC, or multiphysics simulation code is valued.

Skills

Python
PyTorch
JAX
Numerical Simulation
Finite Element Method (FEM)
Computational Fluid Dynamics (CFD)
Multiphysics Modeling
Deep Learning
Surrogate Modeling
Reduced-Order Modeling
Optimization
Design Space Exploration
Physics-Informed Machine Learning
GPU Computing
High-Performance Computing
Prototyping and Benchmarking

Benefits

Collaborative Work Environment
Salary and Benefits Package
Volunteer Day
Inclusion and Wellbeing Initiatives

Visa sponsorship

Not detected in the job text

Keywords

Applied AI
Engineering Simulation
Design Space Exploration
Python
PyTorch
JAX
Machine Learning
Deep Learning
Surrogate Models
Reduced-Order Models
Finite Element Method (FEM)
Computational Fluid Dynamics (CFD)
Multiphysics Modeling
Physics-Informed AI
Scientific Machine Learning
Numerical Simulation
Optimization Workflows
Design of Experiments (DOE)
Parameter Studies
Combinatorial Optimization
GPU Computing
High-Performance Computing (HPC)
Prototyping
Benchmarking
Hybrid Pipelines
High-Fidelity Validation
Robustness Testing
Failure-Mode Analysis
Engineering Workflows
Bentley Systems

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