We are looking for exceptional physicists and engineers who want to turn first-principles thinking into technology used to design the next generation of aircraft, vehicles, chips, and photonic systems.

We welcome outstanding people at different career stages, from exceptional graduates to experienced researchers and engineers. If you want to learn fast, work with unusually strong scientists and engineers, tackle problems at the frontier of computation, and see your work matter in industry, Flexcompute offers a rare environment in which to grow and do your best work.

About Flexcompute

Flexcompute is the physics company. We exist to make the real world computable. Created by engineers from MIT and Stanford, we build trusted, GPU-native physics simulation and AI-powered engineering technology for teams designing aircraft, vehicles, chips, and photonic systems. Our technology is trusted by more than 250 companies and academic institutions, including innovators such as Anduril, BETA Technologies, Coherent, Hermeus, Joby Aviation, Northrop Grumman, Samsung, and Xanadu.

Our products span fluid dynamics, electromagnetics, photonics, geometry, and multiphysics workflows. We work at the frontier of physical modelling, numerical algorithms, GPU computing, high-performance computing, AI, and engineering automation. The goal is not speed at the expense of physics. It is to make previously impractical, high-fidelity engineering work fast enough to shape real design decisions.

About the role

You will join the Flexcompute team in Poland and work at the intersection of physics, engineering, simulation, and technology. The centre of gravity is not writing software for its own sake. It is understanding physical systems and helping turn that understanding into reliable engineering results and better simulation products.

This is not a narrowly defined solver-developer position. Depending on your strengths, you may work closer to customers and applications, simulation validation, product workflows, scientific computing, or a combination of these. Contributions to numerical algorithms or solver development are welcome, but they are not required.

What you will do

• Understand challenging industrial and research problems, identify the relevant physics, and formulate an appropriate simulation strategy.

• Build, run, validate, and interpret simulations in one or more physical domains.

• Investigate unexpected results, convergence behaviour, modelling assumptions, boundary conditions, mesh sensitivity, and discrepancies with experiments or reference data.

• Create clear and reusable Python workflows, examples, benchmarks, and technical demonstrations.

• Collaborate with customers, application engineers, product teams, and solver developers. Translate user needs and physical insight into actionable product feedback.

• Communicate complex engineering ideas clearly through discussions, written explanations, presentations, and technical content.

• Take ownership of difficult, ambiguous problems and drive them toward a trustworthy result.

Two profiles can be equally successful

Application-oriented profile. You have deep physical or engineering understanding, practical simulation experience, strong communication skills, and enough programming ability to automate workflows and investigate problems rigorously.

Scientific-computing profile. You are stronger in numerical methods and technical computing and may contribute more deeply to algorithms, performance, geometry, optimization, or simulation infrastructure.

We do not expect one person to cover both profiles equally. Exceptional strength in physics and applications can compensate for less advanced computing experience.

Working with the Poland team

This role is attached to Flexcompute's Poland office in Katowice. We value regular in-person collaboration, but permanent daily office presence is not required. The working cadence can be agreed based on the role and location. Candidates should be able to spend meaningful time with the Poland team when needed.

Requirements

Who you are

• You have completed, or are close to completing, an MSc or PhD in physics, aerospace engineering, mechanical engineering, computational science, applied mathematics, computer science, or a related technical field.

• You have strong foundations in physics, mathematics, or engineering, can reason from first principles, and have hands-on experience with numerical simulation or quantitative modelling.

• You can write practical scripts, preferably in Python, to automate work, analyse data, and test ideas.

• You are motivated by real engineering problems, product impact, and industrial applications.

• You communicate clearly, learn quickly, and demonstrate unusual ownership, persistence, and intellectual curiosity.

What can demonstrate exceptional ability

We care about evidence of ability and genuine technical interest, not one prescribed career path. Strong signals may include:

• Student engineering teams and competitions: active participation in teams such as SAE Aero Design, Formula Student, rocketry, UAV, robotics, satellite, or other engineering projects.

• Olympiads and technical competitions: national or international physics, mathematics, informatics, astronomy, or engineering competitions.

• Relevant internships or industry experience: placements in aerospace, automotive, energy, advanced manufacturing, research institutes, or industrial R&D.

• Applied research: work that connects modelling with experiments, measurements, design decisions, or a real physical system.

• Personal or open technical work: open-source contributions, simulation tools, automation, technical software, or a demanding project built independently.

Participation alone is not the goal. We are most interested in what you personally designed, simulated, built, tested, debugged, or improved.

Experience that would be useful

Any of the following would be valuable, but none is required across the board:

• CFD, fluid mechanics, aerodynamics, aeroacoustics, heat transfer, structural mechanics, electromagnetics, photonics, quantum physics, or adjacent fields.