Applied Scientist / Research Engineer, AI4Engineering - EMEA, Lausanne
Applied Scientist / Research Engineer, AI4Engineering - EMEA, Lausanne
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Lausanne, Schweiz
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Aufgegeben: vor weniger als einem Monat
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Merken
Anzeigentext
About Mistral At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.
We democratize AI through high-performance, optimized, open-source and cutting‑edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.
We are a dynamic, collaborative team passionate about AI and its potential to transform society.
Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low‑ego and team‑spirited.
Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on Mistral AI is looking for Applied Scientists with deep expertise in engineering sciences to work at the frontier of AI‑accelerated simulation. You will work with industrial customers and internal research teams to build and deploy AI Physics Models alongside our existing offerings of Large Language Models (LLMs).
You will contribute across the full stack: curating high‑fidelity simulation datasets, training and evaluating models, and delivering production‑grade AI solutions directly to engineering teams. Target domains include computational fluid dynamics, structural mechanics, semiconductor design, multi‑physics modelling, and digital twins.
Working cross‑functionally with research, product, and customer‑facing teams, you will ensure our models meet real engineering standards — not just benchmark metrics.
What You Will Do
Design and run large‑scale simulation campaigns using domain‑specific solvers (e.g. OpenFOAM, ANSYS, COMSOL, Abaqus)
Run training of AI models on physics data, with rigorous evaluation of coverage, accuracy, and quality against industry validation standards
Build tools and frameworks for automated dataset creation, simulation pipeline management, and model evaluation
Develop agents and RAG that integrate LLMs with engineering simulation workflows
Collaborate closely with the science/research team on training runs and diagnose failure modes arising from data gaps or architecture limitations
Manage research projects and client communications with engineering teams
About You
Fluent English with excellent communication skills – able to explain technical simulation concepts to both engineering and non‑technical audiences
PhD or Master’s in AI or an engineering science: Mechanical Engineering, Electrical Engineering, Computational Fluid Dynamics, Structural Mechanics, Semiconductor Engineering, or a related field. A solid understanding of deep learning and engineering or physics is a must
Comfortable with PyTorch or JAX for implementing and training models
You write clean, readable Python code and are comfortable in Linux/HPC environments
Self‑directed – you don’t need detailed roadmaps to make progress
Low‑ego, collaborative, and eager to learn at the intersection of simulation and ML
Demonstrated success through industrial projects, academic work, or personal projects
It would be great if you
Have industrial or academic experience with simulation solvers (e.g. OpenFOAM, ANSYS, COMSOL, Abaqus, or equivalent)
Have applied ML methods to simulation or surrogate modelling
Have experience automating large‑scale simulation campaigns on HPC clusters
Have contributed to a large open‑source or industry codebase
Have publications in engineering or ML venues (NeurIPS, ICLR, etc.)
Love improving existing code by fixing typing issues, adding tests and improving CI pipelines
Benefits Locations: Munich, Paris, London, Amsterdam, Lausanne, Linz. Hybrid work model.
France
Competitive cash salary and equity
Daily lunch vouchers
Monthly contribution to a Gympass subscription
Monthly contribution to a mobility pass
Full health insurance for you and your family
Generous parental leave policy
Visa sponsorship
UK
Competitive cash salary and equity
Health insurance
Transportation reimbursement (office parking or£90/month public transport)
£90/month gym membership reimbursement
£200/month meal allowance
Pension plan: SmartPension (5% Employee&3% Employer)
By applying, you agree to our Applicant Privacy Policy.
#J-18808-Ljbffr
We democratize AI through high-performance, optimized, open-source and cutting‑edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.
We are a dynamic, collaborative team passionate about AI and its potential to transform society.
Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low‑ego and team‑spirited.
Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on Mistral AI is looking for Applied Scientists with deep expertise in engineering sciences to work at the frontier of AI‑accelerated simulation. You will work with industrial customers and internal research teams to build and deploy AI Physics Models alongside our existing offerings of Large Language Models (LLMs).
You will contribute across the full stack: curating high‑fidelity simulation datasets, training and evaluating models, and delivering production‑grade AI solutions directly to engineering teams. Target domains include computational fluid dynamics, structural mechanics, semiconductor design, multi‑physics modelling, and digital twins.
Working cross‑functionally with research, product, and customer‑facing teams, you will ensure our models meet real engineering standards — not just benchmark metrics.
What You Will Do
Design and run large‑scale simulation campaigns using domain‑specific solvers (e.g. OpenFOAM, ANSYS, COMSOL, Abaqus)
Run training of AI models on physics data, with rigorous evaluation of coverage, accuracy, and quality against industry validation standards
Build tools and frameworks for automated dataset creation, simulation pipeline management, and model evaluation
Develop agents and RAG that integrate LLMs with engineering simulation workflows
Collaborate closely with the science/research team on training runs and diagnose failure modes arising from data gaps or architecture limitations
Manage research projects and client communications with engineering teams
About You
Fluent English with excellent communication skills – able to explain technical simulation concepts to both engineering and non‑technical audiences
PhD or Master’s in AI or an engineering science: Mechanical Engineering, Electrical Engineering, Computational Fluid Dynamics, Structural Mechanics, Semiconductor Engineering, or a related field. A solid understanding of deep learning and engineering or physics is a must
Comfortable with PyTorch or JAX for implementing and training models
You write clean, readable Python code and are comfortable in Linux/HPC environments
Self‑directed – you don’t need detailed roadmaps to make progress
Low‑ego, collaborative, and eager to learn at the intersection of simulation and ML
Demonstrated success through industrial projects, academic work, or personal projects
It would be great if you
Have industrial or academic experience with simulation solvers (e.g. OpenFOAM, ANSYS, COMSOL, Abaqus, or equivalent)
Have applied ML methods to simulation or surrogate modelling
Have experience automating large‑scale simulation campaigns on HPC clusters
Have contributed to a large open‑source or industry codebase
Have publications in engineering or ML venues (NeurIPS, ICLR, etc.)
Love improving existing code by fixing typing issues, adding tests and improving CI pipelines
Benefits Locations: Munich, Paris, London, Amsterdam, Lausanne, Linz. Hybrid work model.
France
Competitive cash salary and equity
Daily lunch vouchers
Monthly contribution to a Gympass subscription
Monthly contribution to a mobility pass
Full health insurance for you and your family
Generous parental leave policy
Visa sponsorship
UK
Competitive cash salary and equity
Health insurance
Transportation reimbursement (office parking or£90/month public transport)
£90/month gym membership reimbursement
£200/month meal allowance
Pension plan: SmartPension (5% Employee&3% Employer)
By applying, you agree to our Applicant Privacy Policy.
#J-18808-Ljbffr
Highlights
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FirmennameMistral AI
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JobtitelApplied Scientist / Research Engineer, AI4Engineering - EMEA
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