Simulation Engineer - FEA

About the role

In this role, you’ll work closely with our Data Scientists, Machine Learning Engineers, and customers to understand and define the engineering challenges we are solving.

You’ll play a crucial role in delivering high-fidelity simulations by:

• Aid in building complex structural and multi-physics models from geometry clean-up and meshing, to simulating and post-processing complex real-world phenomena, integrating experimental data for model validation.
• Build robust parametric CAD models (NX or CATIA) coupled with simulation pipeline automation through scripting, for executing advanced design optimization and DoE studies.
• Partner with customers to address their most complex engineering challenges through advanced FEA & AI solutions; communicate results clearly.
• Working at the intersection of CAE and Data Science to generate high-quality simulation datasets for training Machine/Deep Learning models. Leveraging data sampling techniques to efficiently capture the design space, reduce computational cost, and enhance model accuracy.
• Accelerate high-fidelity modelling by using Flux (our cloud platform) and on-premise HPC resources, going beyond smart meshing and model setup to achieve real performance gains.
• Document your work through clear technical reports and process notes, contributing to the team's shared knowledge base.
• Traveling domestically and globally (North America, Europe, Asia, Oceania) up to 3-4 weeks per quarter to work side-by-side with customers in building solutions on-site.

Responsibilities

• Aid in building complex structural and multi-physics models from geometry clean-up and meshing, to simulating and post-processing complex real-world phenomena, integrating experimental data for model validation.
• Build robust parametric CAD models (NX or CATIA) coupled with simulation pipeline automation through scripting, for executing advanced design optimization and DoE studies.
• Partner with customers to address their most complex engineering challenges through advanced FEA & AI solutions; communicate results clearly.
• Working at the intersection of CAE and Data Science to generate high-quality simulation datasets for training Machine/Deep Learning models. Leveraging data sampling techniques to efficiently capture the design space, reduce computational cost, and enhance model accuracy.
• Accelerate high-fidelity modelling by using Flux (our cloud platform) and on-premise HPC resources, going beyond smart meshing and model setup to achieve real performance gains.
• Document your work through clear technical reports and process notes, contributing to the team's shared knowledge base.
• Traveling domestically and globally (North America, Europe, Asia, Oceania) up to 3-4 weeks per quarter to work side-by-side with customers in building solutions on-site.

Requirements

With 1-2 years of industry experience (post Masters or PhD) in a commercial, non-research environment, you’re ready to hit the ground running. You’re confident setting up FEA simulations independently, interpreting complex results with depth, and making informed decisions based on solid engineering judgement. Familiarity with turbomachinery analysis, gas turbine, or aircraft structural sizing is a natural fit for this role. Experience with multidisciplinary optimization (MDO) is a bonus, though not essential at this level. In addition, background in composite materials analysis alongside some exposure to damage tolerance and fracture mechanics, would be a strong fit as well.

Qualifications

• Expertise in structural mechanics, and materials science with a solid ability to apply fundamental knowledge to real-world phenomena across a wide range of engineering applications.
• Proficient in at least one of NASTRAN, ABAQUS or ANSYS Mechanical, adept at automating these tools to create scalable optimisation workflows that drive impactful results.
• Exposure to open-source FEA tools (CalculiX, FEniCS), or explicit dynamics (LS-DYNA, Abaqus/Explicit) is a plus.
• Proficiency in parametric CAD modelling (NX or CATIA) and coding in Python, (or the ability to quickly learn programming languages).

Skills

• Strong understanding of finite element analysis (FEA) and its applications in various engineering fields.
• Experience with at least one of the following software packages: NASTRAN, ABAQUS, ANSYS Mechanical.
• Ability to automate FEA tools for creating scalable optimisation workflows.
• Knowledge of open-source FEA tools such as CalculiX, FEniCS, or explicit dynamics tools like LS-DYNA, Abaqus/Explicit.
• Proficiency in parametric CAD modeling (NX or CATIA).
• Experience with Python or the ability to quickly learn programming languages.

Benefits

• Free team lunch 1x/week
• Private health insurance
• Enhanced parental leave
• Annual leave (20 days + public holidays)
• Personal development support
• Gympass / Wellhub (subsidized)
• Flexible Spending Account (FSA)

Pay

Salary for this position is from $138,000 to $217,000

Schedule

Hybrid model blending time together in our New York office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.