As a deep-tech startup, we are looking for talented and passionate people with an appetite for problem solving. Besides the minimal requirements for this job position, your profile is a good fit to our company if you have the following values: High flexibility and adaptability. Tranquility to work under pressure. Appetite for learning and problem solving. Critical thinking. Ability to communicate effectively. Keen to collaboration. Proper time management. Highly autodidact, independent and proactive. Responsibilities: Develop and optimize cutting-edge generative AI models, including large language models (LLMs) and multimodal systems, tailored for SpiNNcloud’s brain-inspired hardware. Actively participate in the planning and execution of scalable AI systems capable of end-to-end model training, tuning, and deployment. Design and implement high-performance AI frameworks and libraries with an emphasis on hardware-awareness and energy efficiency. Perform in-depth analysis of generative AI algorithms to identify opportunities for optimization in terms of accuracy, latency, and energy consumption. Collaborate with researchers and developers to prototype innovative tools and infrastructure for generative AI applications. Contribute to the development of robust APIs and coherent toolsets for seamless integration with SpiNNcloud’s infrastructure. Share impactful findings and results through GitHub repositories, scientific publications, and presentations. Contribute to the development and documentation of demonstrators. Minimum Requirements: Advanced degree (PhD, MSc, or equivalent experience) in Computer Science, Artificial Intelligence, Applied Mathematics, or related fields. Strong mathematical fundamentals and a deep understanding of machine learning algorithms, particularly in generative AI. Proficient programming skills in Python and experience with deep learning frameworks (e.g., PyTorch, JAX). Substantial experience in debugging, performance analysis, and software development best practices. Knowledge of distributed systems and familiarity with scaling AI training pipelines. Experience with Tiny Machine Learning. Added value: Expertise in applying generative AI techniques to LLMs and multimodal models (e.g., image, video, or speech). Hands-on experience with deployment environments and tools like ONNX, Triton, or TensorRT. Familiarity with CPU/GPU architectures and energy-efficient computing techniques. Experience working with neuromorphic or event-based hardware systems (e.g., SpiNNaker). Proven track record of contributing to open-source projects or publications in top-tier conferences. Strong understanding of performance optimization for AI algorithms in hardware-constrained environments. We offer a highly competitive salary with reallocation benefits in a flexible and inclusive work environment. We are an equal opportunity employer, and hence we welcome people of different backgrounds, nationalities, and experiences. Your contact: Hector Andres Gonzalez Diaz Location: SpiNNcloud Systems GmbH, Freiberger Straße 37, 01067 Dresden