Research Scientist

Responsibilities

• Conduct applied research to develop, train, and optimize speech recognition models incorporating NLP, deep learning, and generative AI techniques.
• Design and experiment with LLMs and RAG models for improved conversational AI systems.
• Drive finetuning and domain adaptation strategies for enhancing model performance on multilingual and low-resource speech data.
• Work with agentic AI frameworks to enable advanced workflow orchestration and stateful agent interactions.
• Collaborate with cross-functional teams, including other AI researchers and scientists, to seamlessly integrate features and functionalities.
• Collaborate with engineering teams to implement and deploy scalable cloud-based AI pipelines and services.
• Analyse and preprocess large-scale speech datasets, ensuring high-quality data management for model training.
• Publish research findings in internal and / or external conferences, actively participate in hackathons and contribute to the scientific community.
• Mentor junior researchers and contribute to knowledge sharing and technical leadership within the team.
• What you bring:
• PhD or Master's degree in Computer Science, Electrical Engineering, Computational Linguistics, or related fields.
• Strong expertise in speech recognition, NLP, machine learning, deep learning, and generative AI.
• Experience with end-to-end ASR systems or multi-modal AI models.
• Proven experience with LLMs, retrieval-augmented generation (RAG), and model finetuning.
• Familiarity with agentic AI frameworks and their application in conversational or speech systems.
• Proficiency in Python, deep learning frameworks (PyTorch or TensorFlow), and software engineering best practices.
• Experience with large-scale speech data processing and annotation.
• You possess excellent problem-solving skills, attention to detail, analytical thinking, and a collaborative mindset to work effectively within our fast-paced and innovative environment.
• Excellent communication skills and ability to collaborate across multidisciplinary teams.

Requirements

• Publications in major AI, speech, or NLP conferences.
• Knowledge of distributed computing and containerization (Docker, Kubernetes).

Benefits

Additional Information

A Moving Experience. Do you have a passion for pushing the boundaries of innovation? Are you excited about AI's potential to improve the human experience? Then come join the ride! Who is Cerence ai? Cerence ai is the global leader in AI for transportation, specialized in building AI and voice-powered companions for cars, two-wheelers, and more that enable people to focus on what matters most. With over 500 million cars shipped with Cerence ai technology, we partner with leading automakers (such as Volkswagen, Mercedes, Audi, Toyota and many more), mobility providers, and technology companies to power intuitive, integrated experiences that create safer, more connected, and more enjoyable journeys for drivers and passengers alike. Our Driving Force Our team is dedicated to pushing the boundaries of AI innovation, working around the globe with headquarters in Burlington, Massachusetts, USA and 16 other offices across Europe, Asia, and North America. We bring together diverse backgrounds and varied skill sets with the shared goal of advancing the next generation of transportation user experiences. Our culture is customer-centric, collaborative, fast-paced, and fun, with continuous opportunities for learning and development to support your career growth. Interested in having a significant impact in a dynamic industry with a high-performing global team? We are seeking a highly skilled and innovative Research Scientist specializing in Speech Recognition to drive advanced research and development in NLP, Machine Learning, Deep Learning, generative AI, and large language models (LLMs). This role will focus on building state-of-the-art ASR systems, applying retrieval-augmented generation (RAG) and finetuning techniques, leveraging agentic AI frameworks, and utilizing cloud platforms for scalable deployments. Person should be well-versed in the latest advancements in speech recognition technology, including Generative AI, large language models (LLMs), Agentic AI framework and exposure to Cloud platforms. This role offers a unique opportunity to impact the next generation of speech AI technologies, working with cutting-edge LLMs and agentic AI frameworks under a collaborative and innovative environment.

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