Unikie is a software engineering and innovation company that infuses intelligence into machines, vehicles, and industrial solutions. They enable clients to become leaders in their industries by…
Unikie is a software engineering and innovation company that infuses intelligence into machines, vehicles, and industrial solutions. They enable clients to become leaders in their industries by…
Specialization: Physical AI, embedded software and real-time edge AI
2024 revenue: €65M
Employees (reported): ≈600
Notable investors: CapMan Growth, Tesi, Business Finland
Company Overview
Problem Domain
Autonomy and real-time intelligence for physical systems (vehicles, devices, industrial and defence applications).
Founded
2015
Industry
IT Services and IT Consulting
Funding Track Record
Growth (reported as a growth/Series A round)- 2020-11-19
€12,000,000
Round included Tesi; announced to support international expansion.
Investor Signal
“CapMan Growth, Tesi, Business Finland”
Founders
What we do
Join the Team
AI CFD Simulation Engineer
On-SiteHelsinki, Uusimaa, FI
On-Site • Helsinki, Uusimaa, FI
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WE ARE LOOKING FORAI CFD Simulation Engineer
We seeking an AI CFD (computational fluid dynamics) Simulation Engineer to join the team. This position will support the development and integration of machine-learning and hybrid physics–AI models to accelerate and automate fluid dynamics simulations used in hardware and device design. The role will be in close collaboration with simulation engineers to build intelligent tools and improve design workflows.
Main Responsibilities
Develop hardware acceleration solution to improve CFD simulation efficiency based on OpenFOAM/SU2.
Data processing, data analyzing, feature engineering, AI modeling, and AI model optimizing in the domain of computational fluid dynamics.
Designing and implementing efficient AI algorithm solutions based on domain knowledge and database features to improve simulation efficiency.
Tracking the development of international cutting-edge simulation acceleration technologies, exploring innovative application scenarios of GPU/AI+simulation, and promoting the implementation of technological innovation.
Required Qualifications
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Master's degree or above in computational fluid dynamics, mechanical engineering, applied mathematics, computer science, or a closely related discipline.
Proficient in mathematical foundations such as numerical analysis methods, machine learning theory, probability statistics.
Familiar with the principle of finite element analysis and its application in engineering simulation.
Solid foundation in data structure and algorithm.
Familiar with the principle of LLM and Graph Neural Network.
Proficient in programming languages, such as Python and C++, and have good code development capabilities.
Proficient in the core numerical simulation workflow, include Finite Volume Method (FVM) and Finite Element Method (FEM) algorithms.
Experience with commercial simulation software such as Ansys, Abaqus, COMSOL, and CST is preferred.
Proficient in high-performance computing (HPC) acceleration frameworks such as CUDA, OpenCL, HIP and OpenACC.
Proficient in simulation framework: OpenFOAM or SU2;
Practical experience in AI+ simulation projects is preferred.
Experience in secondary development or solver customization is highly preferred.
Experience in Deep Neural Networks (DNN) or Large Language Models (LLMs) is preferred.
Excellent independent research and problem-solving skills
Good teamwork spirit and communication skills
Highly sensitive to new technologies and continuous learning
Good at summarizing and sharing, and skilled in writing articles and reports.
