Neural Concept
EV Powertrain: Applied AI Engineer
- Location
- Lausanne, Vaud, CH
- Arrangement
- Hybrid
- Employment type
- Full-time
- Posted
- 11 August 2026 (about a month ago)
Checked about a month agoApplications go to the employer, never to RoleSprint
About this role
Applied AI Engineer – EV Powertrain Location: Lausanne, Switzerland or Cambridge, UK
About the role Neural Concept's Vertical Solutions team builds data-driven workflows for specific engineering applications that sit on top of the Neural Concept platform. Working alongside the Solution Owner — who defines product direction and customer value — you bring the deep engineering domain expertise and hands-on technical build capability needed to turn that direction into a working solution. You combine real-world EV Powertrain design experience with fluency in modern AI tooling, including foundation models and LLM-based build assistants, to prototype and ship production-grade workflows quickly.
What you will do
- Build data-driven engineering workflows for EV Powertrain applications (electric motor, gearbox, battery, EDU) on the Neural Concept platform, translating the Solution Owner's product direction into working solutions.
- Work with lead customers to understand and solve their challenges
- Apply deep domain knowledge to ensure workflows reflect real engineering practice, constraints, and edge cases that a non-domain builder would miss.
- Hands-on prototyping using AI/ML tooling — foundation models, LLM-based coding assistants (e.g. Claude), and Python/CAE scripting — to build and iterate rapidly.
- Work day-to-day with CAD/CAE/ML engineers to take prototypes from first pass to production-ready quality.
- Validate outputs against real-world engineering standards, using your domain judgment as the quality bar.
- Feed technical and domain insight back into the broader roadmap based on what you learn while building.
Who you are
- 5+ years of hands-on engineering experience at an OEM or Tier 1 supplier, designing electric motors, gearboxes, batteries, or other EDU sub-systems — system-level experience preferred.
- Fluent in Powertrain simulation tools (Motor-CAD, Maxwell, JMAG, Romax) and/or system-level tools (MATLAB/Simulink, Amesim, or in-house tools).
- Proficient, hands-on user of modern AI tooling — comfortable building real engineering solutions with foundation models and LLM-based tools such as Claude or Codex, not just casually experimenting with them.
- Direct involvement in an AI transformation initiative at your current or previous company — evidence you've driven AI adoption in engineering practice, not just observed it.
- Strong Python (or equivalent) scripting ability to build and connect workflow components yourself.
- Builder mindset: you'd rather prototype something quickly and iterate than stay at the strategy level.
What you get
- Work with a world-class technology team — our engineers are top-notch, and we always aim for excellence.
- Benefit from a competitive salary and rewarding opportunities as we continue to scale.
- Thrive in a collaborative, multicultural environment where your work is visible and recognized.
- Develop professionally alongside talented colleagues who share knowledge freely and support one another.
- Make a global impact by helping customers shift to AI-assisted design, making innovation faster, smarter, and more sustainable.
- Hybrid model and flexible hours — we care about results, not rigid schedules.
WE'RE PROUD TO BE AN EQUAL OPPORTUNITY EMPLOYER, AND WE'RE COMMITTED TO BUILDING A DIVERSE AND INCLUSIVE ENVIRONMENT WHERE YOU CAN THRIVE.
Locations
- Lausanne, Vaud, CH
- Cambridge, GB
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About this listing
Advertised by Neuralconcept and published on Ashby, the applicant tracking system they use.
RoleSprint is not the employer and not a recruiter. Applications are made on the employer’s own site and never reach us; what RoleSprint does is help you decide whether a role is worth your time and prepare for it if it is.
Published 11 August 2026, last checked about a month ago. A posting stops being advertised here 90 days after the employer published it, and one the employer takes down is marked closed rather than quietly removed.