We are looking for an Application Engineer (Multiphysics Simulation) to be the technical bridge between our customers and Allsolve, Quanscient's cloud-native simulation platform. You will work through engineering challenges across structural, thermal, acoustics, electromagnetics, and MEMS and show how they can be solved faster and at greater scale.
In brief
Location: Remote / Tampere / Munich / Glasgow
Type: Full-time, permanent
Domain: Multiphysics simulation, deep tech
Salary: 5000-6500 €/month depending on experience
Website: quanscient.com
Quanscient is a deep-tech company founded in 2021 and based in Tampere. Their cloud-native simulation platform, Allsolve, lets engineering teams run multiphysics simulations across structural, thermal, acoustic, electromagnetic, and MEMS domains, faster and at far greater scale than legacy desktop tools allow. The platform is Python-native, built for cloud, and increasingly AI-integrated. Current customers include leading industrial companies across Europe, North America, and Japan. The team is 40 people from 15 nationalities, working from 17 cities.
In May 2026 Quanscient closed a 10M€ Series A led by 55 North (Danish quantum fund) and B&C Group (Austrian industrial investor), with full re-participation from Maki.vc, Crowberry Capital, QAI Ventures, and First Fellow Partners. The round backs international expansion and the development of what they describe as the first platform to unify simulation, quantum algorithms, and AI.
You will be the technical face of Allsolve, working directly with customers to work through their engineering problems and show how the platform handles them. The work spans the full customer journey, from first evaluation through to onboarding, productive use, and ongoing support.
Beyond the direct customer work, you feed what you learn back into the product. You act as the link between the field and the Solver, ML, and Cloud Infrastructure teams, and you help grow the platform's reach through content, events, and pre-sales support. This is a role for an engineer who enjoys both deep simulation work and working directly with people.
What you'll do
Build, run, and validate multiphysics simulations across structural/mechanical, thermal, acoustics and ultrasound, electromagnetics/RF, and piezoelectric/MEMS domains
Lead technical evaluations and benchmarking studies against analytical models, published literature, and tools such as ANSYS, COMSOL, and Abaqus
Onboard and train new users; deliver demos, webinars, and hands-on workshops that get customers productive quickly
Be the first point of contact for modelling questions, troubleshooting, and best-practice guidance
Develop simulation workflows in the Python SDK, run parameter sweeps and design optimisation, and build AI-driven and agentic workflows alongside surrogate datasets
Support Sales as the technical lead in pre-sales evaluations, scoping customer problems and articulating how the platform delivers value
Act as the voice of the customer toward the Solver, ML, and Cloud Infrastructure teams, translating field learnings into prioritised product feedback
Produce application notes, case studies, and reusable example models
Represent Quanscient at industry events, trade shows, and technical conferences, presenting applied results to engineers and decision-makers
The role sits at the intersection of deep simulation expertise and customer-facing work. You need to be technically credible enough to earn the trust of engineers evaluating the platform, and clear enough in your communication to make complex physics feel approachable.
Must have:
A degree in engineering, physics, or a related field (BSc/MSc; PhD a plus), or equivalent hands-on industrial experience
Demonstrated experience with commercial simulation tools such as ANSYS, COMSOL, or Abaqus
Solid understanding of FEM/FEA and the underlying physics of at least one application domain
Comfortable scripting in Python to automate and scale simulation workflows
Strong customer-facing communication skills, able to explain complex simulation concepts clearly and translate between an engineering problem and the software that solves it
Nice to have:
Domain depth in MEMS, RF/electromagnetics, ultrasound/acoustics/piezoelectrics, or electric motors/superconductors
Prior experience as an Application/Field Application Engineer, Solutions Engineer, or in technical pre-sales
Industry background in semiconductor, MedTech, automotive, aerospace, consumer electronics, or industrial R&D
Familiarity with HPC or cloud simulation workflows
Quanscient is a team of 40 people from 15 nationalities, working from 17 cities. The founders brought together an unusual mix of expertise: world-class simulation algorithms developed over nearly a decade of academic R&D, deep cloud infrastructure experience, and quantum computing research. That foundation is still visible in how the company operates, technically serious, with a low tolerance for nonsense and a genuine respect for hard problems.
The culture is built around the idea that doing good work and enjoying the place you work are not in conflict. The team is distributed and remote work is standard, with people trusted to manage their own time. Decisions get made through open communication rather than hierarchy. The team is international by design, not by accident, and the expectation is that diverse backgrounds make the work better.
If you want to work from an office, there are hubs in Tampere, Munich, and Glasgow
Process
Initial conversation with Ilmiö to map your background and expectations
Introduction with the Quanscient team
Technical discussion or case-based conversation
Final conversation and offer
Interested?
Apply by 12.7.2026 We review applications and move to interviews on a rolling basis, so it is worth applying early.
This job advertisement has been published on behalf of Quanscient by Ilmiö Talent Agency For more information, please contact Mikael Korpi (Talent Partner, Ilmiö), mikael@ilmiotalent.fi
Information about the use of AI in our recruitment process: We use AI to support parts of our recruitment process, such as drafting job descriptions, pre-processing applications, and creating interview notes. AI never makes decisions on its own - all evaluations and hiring decisions are made by humans. Candidate data is processed securely within the EU and is not used to train AI models.
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