Jobs at Cerence

AI That Moves the World. Careers That Move You Forward.

• Define positioning and messaging. Build messaging frameworks, value propositions and differentiated positioning for our products and solutions across automotive, robotics and industrial markets. Connect company strategy, portfolio capabilities, industry use cases, and customer outcomes into compelling product stories that show up consistently across touchpoints.

• Développer et prendre en charge l’un de nos agents spécialisés par domaine, de la conception au déploiement, puis sur le terrain
• Concevoir l’interface d’appel de fonctions qu’un grand modèle de langage utilise pour accomplir des tâches concrètes — régler la climatisation, lancer une chanson ou définir une destination — et la rendre robuste face aux nombreuses façons dont un conducteur peut formuler sa demande

• Design and implement architectures that use state-of-the-art generative AI models for dialog, destination entry, search and many other domains.
• Leverage your expertise to effectively optimize the use of LLMs through prompting or fine-tuning, shaping them for optimal accuracy, naturalness, and performance.

• Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or a related engineering discipline.
• Equivalent practical experience developing edge and embedded applications will also be considered.

• Defining end-to-end Industry 4.0 and Industrial AI solution architectures.
• Shape smart manufacturing platform roadmaps.

• Build applications used directly on factory floors and industrial environments.
• Integrate Cerence SDK and speech technologies into edge devices and operator workflows.

• Own the end-to-end application architecture for humanoid robots.
• Define reusable software platforms spanning robotics, AI, voice, cloud, and edge systems.

• Engage senior technical decision-makers at robotics companies building the next generation of physical AI in mobile and service robotics, from startups to mid-sized players to established names.
• Own the technical core of every opportunity: understand how our voice solution runs on the customer’s hardware, design how it fits, and work through the hard questions that keep a deal moving.

• Optimize and deploy high‑performance LLM inference pipelines
• Own inference runtimes across data center, edge, and embedded platforms

• Suivre les protocoles de sécurité et les formations pour maintenir un environnement de travail sécuritaire
• Respecter les procédures pour signaler toute activité suspecte