Group Leader in Embedded AI – Audio and Language Applications (m/f/d)

The group »Embedded AI« is engaged in optimizing and deploying state-of-the-art deep-learning algorithms for speech and audio technologies as well as natural language processing on embedded devices. The group focuses on enabling real-time AI inference on resource-constrained hardware using modern AI frameworks and runtimes. Key examples include ultra-low-bitrate speech codecs search as NESC and large language models search as ELMOD running directly on smartphones. The team works closely with research groups and customers to ensure efficient deployment, high performance on target devices, short time-to-deployment, and high customer satisfaction. In your position as a Group Leader, you have the following responsibilities: Team Leadership: You lead and develop a highly skilled team of developers working on cutting-edge Embedded AI and Edge AI solutions, fostering technical excellence, collaboration, and innovation in one of the most challenging areas of artificial intelligence. AI Deployment & Optimization: You oversee the implementation, optimization, and deployment of cutting-edge deep-learning algorithms on embedded devices for real-time inference using state-of-the-art AI frameworks and runtimes, supporting internal research teams in translating advanced AI-based signal processing algorithms into deployable embedded solutions. Embedded AI Systems & Hardware Expertise: You acquire and share expert knowledge on new embedded platforms and system-on-chip (SoC) architectures as relevant for deploying AI in heterogeneous computing environments (CPU, GPU, NPU, DSP). Commercialization Support: You coordinate the deployment of AI solutions to customers and support commercialization activities. Cross-Functional Collaboration: You collaborate with internal and external stakeholders to define strategic roadmaps, coordinate deliverables, and ensure successful project execution and customer deployment. Delivery & Performance Management: You manage timelines, deployment targets, and deliverables while ensuring high performance on target devices, short time-to-deployment, and high customer satisfaction.

A Master's degree or equivalent in Electrical Engineering, Computer Science, or a related field. Ideally with courses covering machine learning and deep neural networks (DNN). Good programming skills in C/C++ and Python, with practical experience in DNN frameworks (e.g. PyTorch, TensorFlow) and runtimes (e.g. TVM, ONNX, TFLite, LiteRT). Experience in team leadership and/or project management. Fluent English, with the ability to cooperate effectively in an international, multidisciplinary team. Good to have proficiency in DNN optimization techniques, model compression (e.g., pruning, quantization) and optimization of AI workload wrt. memory, latency, power consumption, and throughput. Background in digital signal processing, particularly for speech and audio processing, and experience in embedded C/C++ development on DSP (ARM, HiFi, Qualcomm), is a plus. Must have good communication skills with the aim of deploying our technology to customers' products.

An exciting role: We offer a diverse and challenging field of work in an international environment, oriented state-of-the-art research and technology. Room for creativity: Projects with strong practical components motivate our employees to drive innovation. Our colleagues enjoy our positive work culture: We are open-minded, we help and trust each other. Top of the line infrastructure at your workplace: State-of-the-art hardware and software in a modern office space support a productive working environment. We value personal contact: our structured onboarding process, you will quickly become familiar with our institute and be able to extend your network successfully. We take your needs seriously: We support your work-life balance by offering flexible working hours and hybrid work. Your goals and interests are important to us: We offer ongoing professional and personal seminars, coaching, and language classes. We offer free parking spaces, charging stations for electric cars, covered bicycle parking, and showers at the institute. In-house health management, including sports courses, running groups, and relaxation seminars. .