Search the 13 jobs at Cerence Inc.

Responsible for developing and implementing advanced AI and speech recognition technologies, optimizing LLMs, conducting data analysis, and collaborating with cross-functional teams for product enhancement.

The Senior Data R&D Engineer will focus on developing and maintaining robust data backend systems for speech recognition and AI models. Responsibilities include text processing, data extraction, building and optimizing data pipelines, and developing research tools to ensure high-quality content processing and relevance. The role also involves scripting, monitoring, testing, and collaborating in an international team.

As a Senior DevOps Engineer, you will implement new cloud features, maintain compliance with product infrastructure, manage and monitor Kubernetes deployments, and handle customer inquiries related to network operations. You will collaborate with team members and enhance the development process while ensuring the security of features in products.

The Senior Data Scientist will architect, design, and implement generative AI models for ASR and TTS applications, leveraging LLMs. Responsibilities include training and optimizing models, collaborating with cross-functional teams, and innovating existing models while staying updated on the latest advancements in generative AI.

As a Senior AI Engineer at Cerence, you will design, develop, and optimize LLM algorithms for automotive embedded systems. Collaborate with teams to integrate LLMs, conduct rigorous testing, stay updated on ML advancements, and enhance performance and capability of automotive AI applications.

As a Senior AI Researcher at Cerence, you will architect and implement advanced generative AI models for ASR and TTS applications, optimizing large language models for accuracy and efficiency. You will collaborate with cross-functional teams to develop customized solutions and stay updated on the latest advancements in AI and language modeling.

The Senior Research Scientist will design, implement, and optimize LLM tools for automotive applications, integrating ML, ASR, and NLP algorithms. Responsibilities include collaborating with teams, validating ML algorithms, and developing tests while staying abreast of ML advancements.

The Senior Research Engineer (NLU) will develop and implement Natural Language Understanding (NLU) models, enhance NLU pipelines, improve model accuracy, and manage quality assurance. The role includes guiding team members and coordinating modeling efforts.

The Senior Research Engineer will design, develop, and optimize Automatic Speech Recognition (ASR) models for automotive applications, ensuring high accuracy and low latency. The role involves assessing ASR system performance in real-world conditions, collaborating with teams for integration, conducting innovative research, and staying updated on advancements in ASR and generative AI.

As a Senior IT System Engineer at Cerence, you will lead software development and system administration efforts, focusing on HPC environments. Responsibilities include managing feature requests, conducting code reviews, and ensuring system performance, while working independently and mentoring junior staff.

As a Principal Software Engineer at Cerence, you will engage in the full development lifecycle of the Studio platform, focusing on designing, implementing, and testing software solutions. You will write Java and Python code, conduct design reviews, and collaborate with the DevOps team, all while advocating for best software practices in an Agile environment.

The Senior Research Engineer will develop and optimize state-of-the-art Automatic Speech Recognition (ASR) models for automotive applications, assess their performance in real-world conditions, collaborate with cross-functional teams, and conduct research on generative AI and LLM advancements to improve voice interaction capabilities.

Lead a team of developers in designing and implementing large language models for Cerence's software products. Collaborate with cross-functional teams to define requirements, create algorithms for model training, and integrate LLM features into voice recognition systems, ensuring high performance and reliability in real-world automotive environments.