AI-Driven CAD/CAE Engineer — Hybrid, Global Impact

Embodied AI; Lausanne; Hybrid; CHF 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work model

Competitive salary

Global impact

Collaborative environment

Job summary

Neural Concept is seeking a Forward Deployed Engineer to collaborate with leading customers in engineering and AI. You will run projects with customer teams, analyze engineering data using Python, and develop tailored workflows that demonstrate AI value across CAD/CAE domains.

You will apply ML workflows to complex engineering problems, deliver proofs-of-concept, and train customer teams to adopt our methods.

Qualifications

• Master’s or PhD in Engineering, Applied Math, or Physics.
• Excellent understanding of both Engineering and Machine Learning.
• Strong Python programming and ML frameworks.
• Experience with simulation and CAD/CAE modelling is a plus.
• Excellent communication skills and customer-facing aptitude.
• English fluency mandatory; French is a plus.

Responsibilities

• Run projects with customer engineering teams, analyze and process engineering data using our platform and Python libraries, and develop tailored solutions.
• Apply machine- and deep-learning workflows to engineering/physics problems and deliver proofs-of-concept in CAD/CAE/manufacturing.
• Train customer teams to effectively use our methods and platform.
• Collaborate with developers to translate customer needs into product improvements.

Skills

Python programming

Machine learning

Deep learning

Communication

English fluency

French (nice-to-have)

Education

Master’s or PhD in Engineering/Applied Math/Physics

Tools

CAD/CAE tools

Python libraries

Job description

Neural Concept is seeking a Forward Deployed Engineer to collaborate with leading customers in engineering and AI. You will run projects with customer teams, analyze engineering data using Python, and develop tailored workflows that demonstrate AI value across CAD/CAE domains.

You will apply ML workflows to complex engineering problems, deliver proofs-of-concept, and train customer teams to adopt our methods.