Computational Solutions Engineer

About Corintis Corintis offers innovative microfluidic cooling technologies for AI chips/GPUs and CPUs used in data centres. Working with many of the world’s largest tech companies, our solutions improve compute sustainability and tackle the excessive electricity consumption associated with data centre cooling, which consumes more electricity than New York and London combined. Ranked as the No.1 Engineering startup in Switzerland for 2025, Corintis offers a friendly and team-oriented workplace, bringing together over 85 people from over 35 nationalities to solve the most significant computing challenges of tomorrow. Based in the EPFL Campus in St. Sulpice, we are closely connected to the local ecosystem and are located a few minutes walk from Lake Geneva. The Role We are looking for a Computational Solutions Engineer who can turn customer inputs into reliable, simulation-ready workflows and deliver high-quality thermal/hydraulic design results. The role centers on building robust end-to-end processes: collecting and structuring customer data, setting up and running multi-fidelity simulations, developing Python tooling for automation, and ensuring that CAD and geometry assets are consistent and manufacturable. You will operate across skived cold plate benchmarks, microfluidic topology optimization, 2.5D/3D CHT simulations, high-fidelity verification, experiment validation, using both in-house tools and external solvers. You will be the technical backbone for project execution maintaining scalable compute setups, troubleshooting environment issues, and ensuring reproducibility across cloud and on-prem systems. The position requires strong quantitative skills and the ability to synthesize results into clear reports, plots, and customer-facing material. Close collaboration with hardware teams and developers is essential, especially when validating designs against prototypes and feeding back improvements to workflows, tools and new features. This is a hands-on role for someone who works independently, communicates clearly, and is comfortable moving between engineering rigor, customer interaction, and practical implementation. Key Responsibilities Customer Input & Setup: Collect and standardize customer requirements (powermaps, geometry constraints, thermal specs). Validate input completeness and prepare simulation-ready configurations. Simulation & Optimization: Run straight-channel benchmarks, inlet/outlet optimization, full topology optimization, 2.5D/3D thermal–hydraulic simulations, and high-fidelity verification using external tools. Python Scripting & Automation: Develop and maintain Python scripts for benchmarking, design sweeps, post-processing, and reporting. Use CLI/terminal workflows to run simulations using in-house tool, manage datasets, and automate repetitive tasks. CAD & Geometry Workflows: Create and update CAD/ECXML files. Maintain template libraries and ensure geometry consistency for manufacturability and prototype validation. Post-Processing & Reporting: Extract results from Paraview, generate comparative plots, and prepare structured reports and slide decks for customers and internal teams. Infrastructure & Tooling: Configure simulation environments on cloud or internal machines (GCP, AWS). Troubleshoot environment, licensing, or workflow issues across Python, ECXML, and remote execution setups. Collaboration & Support: Work with hardware teams on prototype validation, correlate simulations with experiments, and provide reproducible bug reports and feature feedback to the development team. Technical Communication: Create documentation, tutorials, and customer-facing presentations. Support pre-sales discussions with technical evaluations and demonstrations. Requirements - technical expertise Master’s in Mechanical/Thermal Engineering, Aerospace/Computational Engineering, Physics, or similar. ≥3 years of CFD experience with commercial (Ansys, Icepak, Flotherm, Celsius EC, Fidelity) or open-source tools (Python-b